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8 Commits

Author SHA1 Message Date
Ettore Di Giacinto
2aed98d14b add libx11
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-09-28 20:30:31 +02:00
Ettore Di Giacinto
b3a1b3d63f add libxcb
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-09-28 18:59:12 +02:00
Ettore Di Giacinto
e25dd2fe26 debug
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-09-28 18:34:35 +02:00
Ettore Di Giacinto
002f75ac79 ci(tests): drop me. Test vulkan build
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-09-28 18:24:56 +02:00
Ettore Di Giacinto
1ce8f35834 Consume custom vulkan build for arm64
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-09-28 18:20:11 +02:00
Ettore Di Giacinto
be8a314496 Vulkansdk needs sudo
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-09-28 10:01:30 +02:00
Ettore Di Giacinto
406d62d6aa build vulkan manually on arm64
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-09-28 10:01:30 +02:00
Ettore Di Giacinto
9e9f953eec chore(vulkan): enable arm64 image builds
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-09-28 10:01:30 +02:00
350 changed files with 11186 additions and 31440 deletions

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

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@@ -1,288 +0,0 @@
package main
import (
"context"
"fmt"
"os"
"slices"
"strings"
hfapi "github.com/mudler/LocalAI/pkg/huggingface-api"
cogito "github.com/mudler/cogito"
"github.com/mudler/cogito/structures"
"github.com/sashabaranov/go-openai/jsonschema"
)
var (
openAIModel = os.Getenv("OPENAI_MODEL")
openAIKey = os.Getenv("OPENAI_KEY")
openAIBaseURL = os.Getenv("OPENAI_BASE_URL")
galleryIndexPath = os.Getenv("GALLERY_INDEX_PATH")
//defaultclient
llm = cogito.NewOpenAILLM(openAIModel, openAIKey, openAIBaseURL)
)
// cleanTextContent removes trailing spaces, tabs, and normalizes line endings
// to prevent YAML linting issues like trailing spaces and multiple empty lines
func cleanTextContent(text string) string {
lines := strings.Split(text, "\n")
var cleanedLines []string
var prevEmpty bool
for _, line := range lines {
// Remove all trailing whitespace (spaces, tabs, etc.)
trimmed := strings.TrimRight(line, " \t\r")
// Avoid multiple consecutive empty lines
if trimmed == "" {
if !prevEmpty {
cleanedLines = append(cleanedLines, "")
}
prevEmpty = true
} else {
cleanedLines = append(cleanedLines, trimmed)
prevEmpty = false
}
}
// Remove trailing empty lines from the result
result := strings.Join(cleanedLines, "\n")
return strings.TrimRight(result, "\n")
}
// isModelExisting checks if a specific model ID exists in the gallery using text search
func isModelExisting(modelID string) (bool, error) {
indexPath := getGalleryIndexPath()
content, err := os.ReadFile(indexPath)
if err != nil {
return false, fmt.Errorf("failed to read %s: %w", indexPath, err)
}
contentStr := string(content)
// Simple text search - if the model ID appears anywhere in the file, it exists
return strings.Contains(contentStr, modelID), nil
}
// filterExistingModels removes models that already exist in the gallery
func filterExistingModels(models []ProcessedModel) ([]ProcessedModel, error) {
var filteredModels []ProcessedModel
for _, model := range models {
exists, err := isModelExisting(model.ModelID)
if err != nil {
fmt.Printf("Error checking if model %s exists: %v, skipping\n", model.ModelID, err)
continue
}
if !exists {
filteredModels = append(filteredModels, model)
} else {
fmt.Printf("Skipping existing model: %s\n", model.ModelID)
}
}
fmt.Printf("Filtered out %d existing models, %d new models remaining\n",
len(models)-len(filteredModels), len(filteredModels))
return filteredModels, nil
}
// getGalleryIndexPath returns the gallery index file path, with a default fallback
func getGalleryIndexPath() string {
if galleryIndexPath != "" {
return galleryIndexPath
}
return "gallery/index.yaml"
}
func getRealReadme(ctx context.Context, repository string) (string, error) {
// Create a conversation fragment
fragment := cogito.NewEmptyFragment().
AddMessage("user",
`Your task is to get a clear description of a large language model from huggingface by using the provided tool. I will share with you a repository that might be quantized, and as such probably not by the original model author. We need to get the real description of the model, and not the one that might be quantized. You will have to call the tool to get the readme more than once by figuring out from the quantized readme which is the base model readme. This is the repository: `+repository)
// Execute with tools
result, err := cogito.ExecuteTools(llm, fragment,
cogito.WithIterations(3),
cogito.WithMaxAttempts(3),
cogito.WithTools(&HFReadmeTool{client: hfapi.NewClient()}))
if err != nil {
return "", err
}
result = result.AddMessage("user", "Describe the model in a clear and concise way that can be shared in a model gallery.")
// Get a response
newFragment, err := llm.Ask(ctx, result)
if err != nil {
return "", err
}
content := newFragment.LastMessage().Content
return cleanTextContent(content), nil
}
func selectMostInterestingModels(ctx context.Context, searchResult *SearchResult) ([]ProcessedModel, error) {
// Create a conversation fragment
fragment := cogito.NewEmptyFragment().
AddMessage("user",
`Your task is to analyze a list of AI models and select the most interesting ones for a model gallery. You will be given detailed information about multiple models including their metadata, file information, and README content.
Consider the following criteria when selecting models:
1. Model popularity (download count)
2. Model recency (last modified date)
3. Model completeness (has preferred model file, README, etc.)
4. Model uniqueness (not duplicates or very similar models)
5. Model quality (based on README content and description)
6. Model utility (practical applications)
You should select models that would be most valuable for users browsing a model gallery. Prioritize models that are:
- Well-documented with clear READMEs
- Recently updated
- Popular (high download count)
- Have the preferred quantization format available
- Offer unique capabilities or are from reputable authors
Return your analysis and selection reasoning.`)
// Add the search results as context
modelsInfo := fmt.Sprintf("Found %d models matching '%s' with quantization preference '%s':\n\n",
searchResult.TotalModelsFound, searchResult.SearchTerm, searchResult.Quantization)
for i, model := range searchResult.Models {
modelsInfo += fmt.Sprintf("Model %d:\n", i+1)
modelsInfo += fmt.Sprintf(" ID: %s\n", model.ModelID)
modelsInfo += fmt.Sprintf(" Author: %s\n", model.Author)
modelsInfo += fmt.Sprintf(" Downloads: %d\n", model.Downloads)
modelsInfo += fmt.Sprintf(" Last Modified: %s\n", model.LastModified)
modelsInfo += fmt.Sprintf(" Files: %d files\n", len(model.Files))
if model.PreferredModelFile != nil {
modelsInfo += fmt.Sprintf(" Preferred Model File: %s (%d bytes)\n",
model.PreferredModelFile.Path, model.PreferredModelFile.Size)
} else {
modelsInfo += " No preferred model file found\n"
}
if model.ReadmeContent != "" {
modelsInfo += fmt.Sprintf(" README: %s\n", model.ReadmeContent)
}
if model.ProcessingError != "" {
modelsInfo += fmt.Sprintf(" Processing Error: %s\n", model.ProcessingError)
}
modelsInfo += "\n"
}
fragment = fragment.AddMessage("user", modelsInfo)
fragment = fragment.AddMessage("user", "Based on your analysis, select the top 5 most interesting models and provide a brief explanation for each selection. Also, create a filtered SearchResult with only the selected models. Return just a list of repositories IDs, you will later be asked to output it as a JSON array with the json tool.")
// Get a response
newFragment, err := llm.Ask(ctx, fragment)
if err != nil {
return nil, err
}
fmt.Println(newFragment.LastMessage().Content)
repositories := struct {
Repositories []string `json:"repositories"`
}{}
s := structures.Structure{
Schema: jsonschema.Definition{
Type: jsonschema.Object,
AdditionalProperties: false,
Properties: map[string]jsonschema.Definition{
"repositories": {
Type: jsonschema.Array,
Items: &jsonschema.Definition{Type: jsonschema.String},
Description: "The trending repositories IDs",
},
},
Required: []string{"repositories"},
},
Object: &repositories,
}
err = newFragment.ExtractStructure(ctx, llm, s)
if err != nil {
return nil, err
}
filteredModels := []ProcessedModel{}
for _, m := range searchResult.Models {
if slices.Contains(repositories.Repositories, m.ModelID) {
filteredModels = append(filteredModels, m)
}
}
return filteredModels, nil
}
// ModelFamily represents a YAML anchor/family
type ModelFamily struct {
Anchor string `json:"anchor"`
Name string `json:"name"`
}
// selectModelFamily selects the appropriate model family/anchor for a given model
func selectModelFamily(ctx context.Context, model ProcessedModel, availableFamilies []ModelFamily) (string, error) {
// Create a conversation fragment
fragment := cogito.NewEmptyFragment().
AddMessage("user",
`Your task is to select the most appropriate model family/anchor for a given AI model. You will be provided with:
1. Information about the model (name, description, etc.)
2. A list of available model families/anchors
You need to select the family that best matches the model's architecture, capabilities, or characteristics. Consider:
- Model architecture (e.g., Llama, Qwen, Mistral, etc.)
- Model capabilities (e.g., vision, coding, chat, etc.)
- Model size/type (e.g., small, medium, large)
- Model purpose (e.g., general purpose, specialized, etc.)
Return the anchor name that best fits the model.`)
// 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)
modelInfo += fmt.Sprintf(" Description: %s\n", model.ReadmeContentPreview)
fragment = fragment.AddMessage("user", modelInfo)
// Add available families
familiesInfo := "Available Model Families:\n"
for _, family := range availableFamilies {
familiesInfo += fmt.Sprintf(" - %s (%s)\n", family.Anchor, family.Name)
}
fragment = fragment.AddMessage("user", familiesInfo)
fragment = fragment.AddMessage("user", "Select the most appropriate family anchor for this model. Return just the anchor name.")
// Get a response
newFragment, err := llm.Ask(ctx, fragment)
if err != nil {
return "", err
}
// Extract the selected family
selectedFamily := strings.TrimSpace(newFragment.LastMessage().Content)
// Validate that the selected family exists in our list
for _, family := range availableFamilies {
if family.Anchor == selectedFamily {
return selectedFamily, nil
}
}
// If no exact match, try to find a close match
for _, family := range availableFamilies {
if strings.Contains(strings.ToLower(family.Anchor), strings.ToLower(selectedFamily)) ||
strings.Contains(strings.ToLower(selectedFamily), strings.ToLower(family.Anchor)) {
return family.Anchor, nil
}
}
// Default fallback
return "llama3", nil
}

View File

@@ -1,203 +0,0 @@
package main
import (
"context"
"fmt"
"os"
"strings"
)
// generateYAMLEntry generates a YAML entry for a model using the specified anchor
func generateYAMLEntry(model ProcessedModel, familyAnchor string) string {
// 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", "")
fileName := ""
checksum := ""
if model.PreferredModelFile != nil {
fileParts := strings.Split(model.PreferredModelFile.Path, "/")
if len(fileParts) > 0 {
fileName = fileParts[len(fileParts)-1]
}
checksum = model.PreferredModelFile.SHA256
} else {
fileName = model.ModelID
}
description := model.ReadmeContent
if description == "" {
description = fmt.Sprintf("AI model: %s", modelName)
}
// Clean up description to prevent YAML linting issues
description = cleanTextContent(description)
// Format description for YAML (indent each line and ensure no trailing spaces)
lines := strings.Split(description, "\n")
var formattedLines []string
for _, line := range lines {
if strings.TrimSpace(line) == "" {
// Keep empty lines as empty (no indentation)
formattedLines = append(formattedLines, "")
} else {
// Add indentation to non-empty lines
formattedLines = append(formattedLines, " "+line)
}
}
formattedDescription := strings.Join(formattedLines, "\n")
// Remove any trailing spaces from the formatted description
formattedDescription = strings.TrimRight(formattedDescription, " \t")
yamlTemplate := ""
if checksum != "" {
yamlTemplate = `- !!merge <<: *%s
name: "%s"
urls:
- https://huggingface.co/%s
description: |
%s
overrides:
parameters:
model: %s
files:
- filename: %s
sha256: %s
uri: huggingface://%s/%s`
return fmt.Sprintf(yamlTemplate,
familyAnchor,
modelName,
model.ModelID,
formattedDescription,
fileName,
fileName,
checksum,
model.ModelID,
fileName,
)
} else {
yamlTemplate = `- !!merge <<: *%s
name: "%s"
urls:
- https://huggingface.co/%s
description: |
%s
overrides:
parameters:
model: %s`
return fmt.Sprintf(yamlTemplate,
familyAnchor,
modelName,
model.ModelID,
formattedDescription,
fileName,
)
}
}
// extractModelFamilies extracts all YAML anchors from the gallery index.yaml file
func extractModelFamilies() ([]ModelFamily, error) {
// Read the index.yaml file
indexPath := getGalleryIndexPath()
content, err := os.ReadFile(indexPath)
if err != nil {
return nil, fmt.Errorf("failed to read %s: %w", indexPath, err)
}
lines := strings.Split(string(content), "\n")
var families []ModelFamily
for _, line := range lines {
line = strings.TrimSpace(line)
// Look for YAML anchors (lines starting with "- &")
if strings.HasPrefix(line, "- &") {
// Extract the anchor name (everything after "- &")
anchor := strings.TrimPrefix(line, "- &")
// Remove any trailing colon or other characters
anchor = strings.Split(anchor, ":")[0]
anchor = strings.Split(anchor, " ")[0]
if anchor != "" {
families = append(families, ModelFamily{
Anchor: anchor,
Name: anchor, // Use anchor as name for now
})
}
}
}
return families, nil
}
// generateYAMLForModels generates YAML entries for selected models and appends to index.yaml
func generateYAMLForModels(ctx context.Context, models []ProcessedModel) error {
// Extract available model families
families, err := extractModelFamilies()
if err != nil {
return fmt.Errorf("failed to extract model families: %w", err)
}
fmt.Printf("Found %d model families: %v\n", len(families),
func() []string {
var names []string
for _, f := range families {
names = append(names, f.Anchor)
}
return names
}())
// Generate YAML entries for each model
var yamlEntries []string
for _, model := range models {
fmt.Printf("Selecting family for model: %s\n", model.ModelID)
// Select appropriate family for this model
familyAnchor, err := selectModelFamily(ctx, model, families)
if err != nil {
fmt.Printf("Error selecting family for %s: %v, using default\n", model.ModelID, err)
familyAnchor = "llama3" // Default fallback
}
fmt.Printf("Selected family '%s' for model %s\n", familyAnchor, model.ModelID)
// Generate YAML entry
yamlEntry := generateYAMLEntry(model, familyAnchor)
yamlEntries = append(yamlEntries, yamlEntry)
}
// Append to index.yaml
if len(yamlEntries) > 0 {
indexPath := getGalleryIndexPath()
fmt.Printf("Appending 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)
}
// Append new entries
// Remove trailing whitespace from existing content and join entries without extra newlines
existingContent := strings.TrimRight(string(content), " \t\n\r")
yamlBlock := strings.Join(yamlEntries, "\n")
newContent := existingContent + "\n" + yamlBlock + "\n"
// 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 added %d models to %s\n", len(yamlEntries), indexPath)
}
return nil
}

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@@ -1,351 +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"`
}
// SearchResult represents the complete result of searching and processing models
type SearchResult struct {
SearchTerm string `json:"search_term"`
Limit int `json:"limit"`
Quantization string `json:"quantization"`
TotalModelsFound int `json:"total_models_found"`
Models []ProcessedModel `json:"models"`
FormattedOutput string `json:"formatted_output"`
}
// AddedModelSummary represents a summary of models added to the gallery
type AddedModelSummary struct {
SearchTerm string `json:"search_term"`
TotalFound int `json:"total_found"`
ModelsAdded int `json:"models_added"`
AddedModelIDs []string `json:"added_model_ids"`
AddedModelURLs []string `json:"added_model_urls"`
Quantization string `json:"quantization"`
ProcessingTime string `json:"processing_time"`
}
func main() {
startTime := time.Now()
// Check for synthetic mode
syntheticMode := os.Getenv("SYNTHETIC_MODE")
if syntheticMode == "true" || syntheticMode == "1" {
fmt.Println("Running in SYNTHETIC MODE - generating random test data")
err := runSyntheticMode()
if err != nil {
fmt.Fprintf(os.Stderr, "Error in synthetic mode: %v\n", err)
os.Exit(1)
}
return
}
// Get configuration from environment variables
searchTerm := os.Getenv("SEARCH_TERM")
if searchTerm == "" {
searchTerm = "GGUF"
}
limitStr := os.Getenv("LIMIT")
if limitStr == "" {
limitStr = "5"
}
limit, err := strconv.Atoi(limitStr)
if err != nil {
fmt.Fprintf(os.Stderr, "Error parsing LIMIT: %v\n", err)
os.Exit(1)
}
quantization := os.Getenv("QUANTIZATION")
maxModels := os.Getenv("MAX_MODELS")
if maxModels == "" {
maxModels = "1"
}
maxModelsInt, err := strconv.Atoi(maxModels)
if err != nil {
fmt.Fprintf(os.Stderr, "Error parsing MAX_MODELS: %v\n", err)
os.Exit(1)
}
// Print configuration
fmt.Printf("Gallery Agent Configuration:\n")
fmt.Printf(" Search Term: %s\n", searchTerm)
fmt.Printf(" Limit: %d\n", limit)
fmt.Printf(" Quantization: %s\n", quantization)
fmt.Printf(" Max Models to Add: %d\n", maxModelsInt)
fmt.Printf(" Gallery Index Path: %s\n", os.Getenv("GALLERY_INDEX_PATH"))
fmt.Println()
result, err := searchAndProcessModels(searchTerm, limit, quantization)
if err != nil {
fmt.Fprintf(os.Stderr, "Error: %v\n", err)
os.Exit(1)
}
fmt.Println(result.FormattedOutput)
// Use AI agent to select the most interesting models
fmt.Println("Using AI agent to select the most interesting models...")
models, err := selectMostInterestingModels(context.Background(), result)
if err != nil {
fmt.Fprintf(os.Stderr, "Error in model selection: %v\n", err)
// Continue with original result if selection fails
models = result.Models
}
fmt.Print(models)
// Filter out models that already exist in the gallery
fmt.Println("Filtering out existing models...")
models, err = filterExistingModels(models)
if err != nil {
fmt.Fprintf(os.Stderr, "Error filtering existing models: %v\n", err)
os.Exit(1)
}
// Limit to maxModelsInt after filtering
if len(models) > maxModelsInt {
models = models[:maxModelsInt]
}
// Track added models for summary
var addedModelIDs []string
var addedModelURLs []string
// Generate YAML entries and append to gallery/index.yaml
if len(models) > 0 {
for _, model := range models {
addedModelIDs = append(addedModelIDs, model.ModelID)
// Generate Hugging Face URL for the model
modelURL := fmt.Sprintf("https://huggingface.co/%s", model.ModelID)
addedModelURLs = append(addedModelURLs, modelURL)
}
fmt.Println("Generating YAML entries for selected models...")
err = generateYAMLForModels(context.Background(), models)
if err != nil {
fmt.Fprintf(os.Stderr, "Error generating YAML entries: %v\n", err)
os.Exit(1)
}
} else {
fmt.Println("No new models to add to the gallery.")
}
// Create and write summary
processingTime := time.Since(startTime).String()
summary := AddedModelSummary{
SearchTerm: searchTerm,
TotalFound: result.TotalModelsFound,
ModelsAdded: len(addedModelIDs),
AddedModelIDs: addedModelIDs,
AddedModelURLs: addedModelURLs,
Quantization: quantization,
ProcessingTime: processingTime,
}
// Write summary to file
summaryData, err := json.MarshalIndent(summary, "", " ")
if err != nil {
fmt.Fprintf(os.Stderr, "Error marshaling summary: %v\n", err)
} else {
err = os.WriteFile("gallery-agent-summary.json", summaryData, 0644)
if err != nil {
fmt.Fprintf(os.Stderr, "Error writing summary file: %v\n", err)
} else {
fmt.Printf("Summary written to gallery-agent-summary.json\n")
}
}
}
func searchAndProcessModels(searchTerm string, limit int, quantization string) (*SearchResult, error) {
client := hfapi.NewClient()
var outputBuilder strings.Builder
fmt.Println("Searching for models...")
// Initialize the result struct
result := &SearchResult{
SearchTerm: searchTerm,
Limit: limit,
Quantization: quantization,
Models: []ProcessedModel{},
}
models, err := client.GetLatest(searchTerm, limit)
if err != nil {
return nil, fmt.Errorf("failed to fetch models: %w", err)
}
fmt.Println("Models found:", len(models))
result.TotalModelsFound = len(models)
if len(models) == 0 {
outputBuilder.WriteString("No models found.\n")
result.FormattedOutput = outputBuilder.String()
return result, nil
}
outputBuilder.WriteString(fmt.Sprintf("Found %d models matching '%s':\n\n", len(models), searchTerm))
// Process each model
for i, model := range models {
outputBuilder.WriteString(fmt.Sprintf("%d. Processing Model: %s\n", i+1, model.ModelID))
outputBuilder.WriteString(fmt.Sprintf(" Author: %s\n", model.Author))
outputBuilder.WriteString(fmt.Sprintf(" Downloads: %d\n", model.Downloads))
outputBuilder.WriteString(fmt.Sprintf(" Last Modified: %s\n", model.LastModified))
// Initialize processed model struct
processedModel := ProcessedModel{
ModelID: model.ModelID,
Author: model.Author,
Downloads: model.Downloads,
LastModified: model.LastModified,
QuantizationPreferences: []string{quantization, "Q4_K_M", "Q4_K_S", "Q3_K_M", "Q2_K"},
}
// Get detailed model information
details, err := client.GetModelDetails(model.ModelID)
if err != nil {
errorMsg := fmt.Sprintf(" Error getting model details: %v\n", err)
outputBuilder.WriteString(errorMsg)
processedModel.ProcessingError = err.Error()
result.Models = append(result.Models, processedModel)
continue
}
// Define quantization preferences (in order of preference)
quantizationPreferences := []string{quantization, "Q4_K_M", "Q4_K_S", "Q3_K_M", "Q2_K"}
// Find preferred model file
preferredModelFile := hfapi.FindPreferredModelFile(details.Files, quantizationPreferences)
// Process files
processedFiles := make([]ProcessedModelFile, len(details.Files))
for j, file := range details.Files {
fileType := "other"
if file.IsReadme {
fileType = "readme"
} else if preferredModelFile != nil && file.Path == preferredModelFile.Path {
fileType = "model"
}
processedFiles[j] = ProcessedModelFile{
Path: file.Path,
Size: file.Size,
SHA256: file.SHA256,
IsReadme: file.IsReadme,
FileType: fileType,
}
}
processedModel.Files = processedFiles
// Set preferred model file
if preferredModelFile != nil {
for _, file := range processedFiles {
if file.Path == preferredModelFile.Path {
processedModel.PreferredModelFile = &file
break
}
}
}
// Print file information
outputBuilder.WriteString(fmt.Sprintf(" Files found: %d\n", len(details.Files)))
if preferredModelFile != nil {
outputBuilder.WriteString(fmt.Sprintf(" Preferred Model File: %s (SHA256: %s)\n",
preferredModelFile.Path,
preferredModelFile.SHA256))
} else {
outputBuilder.WriteString(fmt.Sprintf(" No model file found with quantization preferences: %v\n", quantizationPreferences))
}
if details.ReadmeFile != nil {
outputBuilder.WriteString(fmt.Sprintf(" README File: %s\n", details.ReadmeFile.Path))
// Find and set readme file
for _, file := range processedFiles {
if file.IsReadme {
processedModel.ReadmeFile = &file
break
}
}
fmt.Println("Getting real readme for", model.ModelID, "waiting...")
// Use agent to get the real readme and prepare the model description
readmeContent, err := getRealReadme(context.Background(), model.ModelID)
if err == nil {
processedModel.ReadmeContent = readmeContent
processedModel.ReadmeContentPreview = truncateString(readmeContent, 200)
outputBuilder.WriteString(fmt.Sprintf(" README Content Preview: %s\n",
processedModel.ReadmeContentPreview))
} else {
continue
}
fmt.Println("Real readme got", readmeContent)
// 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

@@ -1,190 +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)
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)
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: "",
}
}
// 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) 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"},
},
},
}
}

View File

File diff suppressed because it is too large Load Diff

View File

@@ -97,7 +97,7 @@ jobs:
&& sudo apt-get install -y git
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v5
- name: Release space from worker
if: inputs.runs-on == 'ubuntu-latest'

View File

@@ -50,7 +50,7 @@ jobs:
go-version: ['${{ inputs.go-version }}']
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
submodules: true
@@ -74,7 +74,7 @@ jobs:
BACKEND=${{ 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@v5
uses: actions/upload-artifact@v4
with:
name: ${{ inputs.backend }}-tar
path: backend-images/${{ inputs.backend }}.tar
@@ -85,7 +85,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Download ${{ inputs.backend }}.tar
uses: actions/download-artifact@v6
uses: actions/download-artifact@v5
with:
name: ${{ inputs.backend }}-tar
path: .

View File

@@ -17,7 +17,7 @@ jobs:
has-backends-darwin: ${{ steps.set-matrix.outputs.has-backends-darwin }}
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v5
- name: Setup Bun
uses: oven-sh/setup-bun@v2

View File

@@ -11,13 +11,13 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.25
go-version: 1.23
- name: Run GoReleaser
run: |
make dev-dist
@@ -25,19 +25,19 @@ jobs:
runs-on: macos-latest
steps:
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.25
go-version: 1.23
- name: Build launcher for macOS ARM64
run: |
make build-launcher-darwin
ls -liah dist
- name: Upload macOS launcher artifacts
uses: actions/upload-artifact@v5
uses: actions/upload-artifact@v4
with:
name: launcher-macos
path: dist/
@@ -47,20 +47,20 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.25
go-version: 1.23
- 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@v5
uses: actions/upload-artifact@v4
with:
name: launcher-linux
path: local-ai-launcher-linux.tar.xz

View File

@@ -1,10 +1,10 @@
name: Bump Backend dependencies
name: Bump dependencies
on:
schedule:
- cron: 0 20 * * *
workflow_dispatch:
jobs:
bump-backends:
bump:
strategy:
fail-fast: false
matrix:
@@ -31,7 +31,7 @@ jobs:
file: "backend/go/piper/Makefile"
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
- name: Bump dependencies 🔧
id: bump
run: |

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:
@@ -12,7 +12,7 @@ jobs:
- repository: "mudler/LocalAI"
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
- name: Bump dependencies 🔧
run: |
bash .github/bump_docs.sh ${{ matrix.repository }}

View File

@@ -15,7 +15,7 @@ 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@v5
- name: Install dependencies
run: |
sudo apt-get update

View File

@@ -20,7 +20,7 @@ jobs:
skip-commit-verification: true
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v5
- name: Approve a PR if not already approved
run: |

View File

@@ -15,7 +15,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
submodules: true
- uses: actions/setup-go@v5
@@ -33,7 +33,7 @@ jobs:
run: |
CGO_ENABLED=0 make build
- name: rm
uses: appleboy/ssh-action@v1.2.3
uses: appleboy/ssh-action@v1.2.2
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}
@@ -53,7 +53,7 @@ jobs:
rm: true
target: ./local-ai
- name: restarting
uses: appleboy/ssh-action@v1.2.3
uses: appleboy/ssh-action@v1.2.2
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}

View File

@@ -1,119 +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: Run gallery agent
env:
OPENAI_MODEL: ${{ secrets.OPENAI_MODEL }}
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 ".github/gallery-agent/gallery-agent-summary.json" ]; then
echo "summary_exists=true" >> $GITHUB_OUTPUT
# Extract summary data using jq
echo "search_term=$(jq -r '.search_term' .github/gallery-agent/gallery-agent-summary.json)" >> $GITHUB_OUTPUT
echo "total_found=$(jq -r '.total_found' .github/gallery-agent/gallery-agent-summary.json)" >> $GITHUB_OUTPUT
echo "models_added=$(jq -r '.models_added' .github/gallery-agent/gallery-agent-summary.json)" >> $GITHUB_OUTPUT
echo "quantization=$(jq -r '.quantization' .github/gallery-agent/gallery-agent-summary.json)" >> $GITHUB_OUTPUT
echo "processing_time=$(jq -r '.processing_time' .github/gallery-agent/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]))"' .github/gallery-agent/gallery-agent-summary.json | tr '\n' '\n')
echo "added_models<<EOF" >> $GITHUB_OUTPUT
echo "$added_models" >> $GITHUB_OUTPUT
echo "EOF" >> $GITHUB_OUTPUT
rm -f .github/gallery-agent/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@v7
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

@@ -73,7 +73,7 @@ jobs:
uses: docker/setup-buildx-action@master
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v5
- name: Cache GRPC
uses: docker/build-push-action@v6

View File

@@ -16,7 +16,7 @@ jobs:
matrix:
include:
- base-image: intel/oneapi-basekit:2025.2.0-0-devel-ubuntu22.04
runs-on: 'arc-runner-set'
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@v5
- name: Cache Intel images
uses: docker/build-push-action@v6

View File

@@ -60,7 +60,7 @@ jobs:
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'vulkan'
platforms: 'linux/amd64'
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'false'
tag-suffix: '-vulkan-core'
runs-on: 'ubuntu-latest'

View File

@@ -101,7 +101,7 @@ jobs:
makeflags: "--jobs=4 --output-sync=target"
aio: "-aio-gpu-nvidia-cuda-12"
- build-type: 'vulkan'
platforms: 'linux/amd64'
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'auto'
tag-suffix: '-gpu-vulkan'
runs-on: 'ubuntu-latest'

View File

@@ -94,7 +94,7 @@ jobs:
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v5
- name: Release space from worker
if: inputs.runs-on == 'ubuntu-latest'

View File

@@ -11,10 +11,10 @@ permissions:
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@v5
- name: Approve a PR if not already approved
run: |

View File

@@ -1,27 +1,22 @@
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: gemma-3-12b-it
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
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: 'gemma-3-12b-it' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
# Check the PR diff using the current branch and the base branch of the PR
- uses: GrantBirki/git-diff-action@v2.8.1
id: git-diff-action
@@ -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@v3.22
with:
detached: true
connect-timeout-seconds: 180
@@ -92,13 +87,12 @@ 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: gemma-3-12b-it
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
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..."
@@ -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@v3.22
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: 'gemma-3-12b-it' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
- name: Summarize
id: summarize
run: |

View File

@@ -10,7 +10,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
fetch-depth: 0
- name: Set up Go
@@ -28,7 +28,7 @@ jobs:
runs-on: macos-latest
steps:
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
fetch-depth: 0
- name: Set up Go
@@ -46,7 +46,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
fetch-depth: 0
- name: Set up Go

View File

@@ -14,7 +14,7 @@ jobs:
GO111MODULE: on
steps:
- name: Checkout Source
uses: actions/checkout@v6
uses: actions/checkout@v5
if: ${{ github.actor != 'dependabot[bot]' }}
- name: Run Gosec Security Scanner
if: ${{ github.actor != 'dependabot[bot]' }}
@@ -24,7 +24,7 @@ jobs:
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

@@ -10,7 +10,7 @@ jobs:
stale:
runs-on: ubuntu-latest
steps:
- uses: actions/stale@5f858e3efba33a5ca4407a664cc011ad407f2008 # v9
- uses: actions/stale@3a9db7e6a41a89f618792c92c0e97cc736e1b13f # 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.'

View File

@@ -19,7 +19,7 @@ jobs:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# uses: actions/checkout@v5
# with:
# submodules: true
# - name: Dependencies
@@ -40,7 +40,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
submodules: true
- name: Dependencies
@@ -61,7 +61,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
submodules: true
- name: Dependencies
@@ -83,7 +83,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
submodules: true
- name: Dependencies
@@ -104,7 +104,7 @@ jobs:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# uses: actions/checkout@v5
# with:
# submodules: true
# - name: Dependencies
@@ -124,7 +124,7 @@ jobs:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# uses: actions/checkout@v5
# with:
# submodules: true
# - name: Dependencies
@@ -186,7 +186,7 @@ jobs:
# sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
# df -h
# - name: Clone
# uses: actions/checkout@v6
# uses: actions/checkout@v5
# with:
# submodules: true
# - name: Dependencies
@@ -211,7 +211,7 @@ jobs:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# uses: actions/checkout@v5
# with:
# submodules: true
# - name: Dependencies
@@ -232,7 +232,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
submodules: true
- name: Dependencies

View File

@@ -21,7 +21,7 @@ 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
@@ -70,7 +70,7 @@ jobs:
sudo rm -rfv build || true
df -h
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
@@ -124,7 +124,7 @@ jobs:
PATH="$PATH:/root/go/bin" GO_TAGS="tts" make --jobs 5 --output-sync=target test
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
uses: mxschmitt/action-tmate@v3.22
with:
detached: true
connect-timeout-seconds: 180
@@ -166,7 +166,7 @@ jobs:
sudo rm -rfv build || true
df -h
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v5
with:
submodules: true
- name: Dependencies
@@ -183,7 +183,7 @@ jobs:
PATH="$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
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
uses: mxschmitt/action-tmate@v3.22
with:
detached: true
connect-timeout-seconds: 180
@@ -193,10 +193,10 @@ jobs:
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@v5
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
@@ -226,7 +226,7 @@ jobs:
PATH="$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
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
uses: mxschmitt/action-tmate@v3.22
with:
detached: true
connect-timeout-seconds: 180

View File

@@ -9,7 +9,7 @@ jobs:
fail-fast: false
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v5
- uses: actions/setup-go@v5
with:
go-version: 'stable'

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

@@ -30,7 +30,6 @@ Thank you for your interest in contributing to LocalAI! We appreciate your time
3. Install the required dependencies ( see https://localai.io/basics/build/#build-localai-locally )
4. Build LocalAI: `make build`
5. Run LocalAI: `./local-ai`
6. To Build and live reload: `make build-dev`
## Contributing
@@ -77,7 +76,7 @@ LOCALAI_IMAGE_TAG=test LOCALAI_IMAGE=local-ai-aio make run-e2e-aio
## Documentation
We are welcome the contribution of the documents, please open new PR or create a new issue. The documentation is available under `docs/` https://github.com/mudler/LocalAI/tree/master/docs
## Community and Communication
- You can reach out via the Github issue tracker.

View File

@@ -32,15 +32,27 @@ RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt-get update && \
apt-get install -y \
vulkan-sdk && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
echo "vulkan" > /run/localai/capability
software-properties-common pciutils sudo wget gpg-agent curl xz-utils && \
echo "vulkan" > /run/localai/capability && \
if [ "amd64" = "$TARGETARCH" ]; then
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt-get update && \
apt-get install -y \
vulkan-sdk && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
if [ "arm64" = "$TARGETARCH" ]; then
# For ARM64, we need to build the Vulkan SDK manually as there are no packages available
mkdir vulkan && cd vulkan && curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.321.1/vulkansdk-ubuntu-22.04-arm-1.4.321.1.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd * && \
cp -rfv aarch64/* /usr/ && \
cd ../.. && \
rm -rf vulkan
fi
fi
EOT
@@ -332,6 +344,6 @@ RUN mkdir -p /models /backends
HEALTHCHECK --interval=1m --timeout=10m --retries=10 \
CMD curl -f ${HEALTHCHECK_ENDPOINT} || exit 1
VOLUME /models /backends /configuration
VOLUME /models /backends
EXPOSE 8080
ENTRYPOINT [ "/entrypoint.sh" ]

View File

@@ -103,10 +103,6 @@ build-launcher: ## Build the launcher application
build-all: build build-launcher ## Build both server and launcher
build-dev: ## Run LocalAI in dev mode with live reload
@command -v air >/dev/null 2>&1 || go install github.com/air-verse/air@latest
air -c .air.toml
dev-dist:
$(GORELEASER) build --snapshot --clean
@@ -380,9 +376,6 @@ backends/llama-cpp-darwin: build
bash ./scripts/build/llama-cpp-darwin.sh
./local-ai backends install "ocifile://$(abspath ./backend-images/llama-cpp.tar)"
backends/neutts: docker-build-neutts docker-save-neutts build
./local-ai backends install "ocifile://$(abspath ./backend-images/neutts.tar)"
build-darwin-python-backend: build
bash ./scripts/build/python-darwin.sh
@@ -439,12 +432,6 @@ docker-save-kitten-tts: backend-images
docker-save-chatterbox: backend-images
docker save local-ai-backend:chatterbox -o backend-images/chatterbox.tar
docker-build-neutts:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:neutts -f backend/Dockerfile.python --build-arg BACKEND=neutts ./backend
docker-save-neutts: backend-images
docker save local-ai-backend:neutts -o backend-images/neutts.tar
docker-build-kokoro:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:kokoro -f backend/Dockerfile.python --build-arg BACKEND=kokoro ./backend

View File

@@ -43,7 +43,7 @@
> :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
> [💻 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) [🌍 Explorer](https://explorer.localai.io) [🛫 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)
[![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)
@@ -108,7 +108,7 @@ Run the installer script:
curl https://localai.io/install.sh | sh
```
For more installation options, see [Installer Options](https://localai.io/installation/).
For more installation options, see [Installer Options](https://localai.io/docs/advanced/installer/).
### macOS Download:
@@ -116,17 +116,8 @@ For more installation options, see [Installer Options](https://localai.io/instal
<img src="https://img.shields.io/badge/Download-macOS-blue?style=for-the-badge&logo=apple&logoColor=white" alt="Download LocalAI for macOS"/>
</a>
> Note: the DMGs are not signed by Apple as quarantined. See https://github.com/mudler/LocalAI/issues/6268 for a workaround, fix is tracked here: https://github.com/mudler/LocalAI/issues/6244
Or run with docker:
> **💡 Docker Run vs Docker Start**
>
> - `docker run` creates and starts a new container. If a container with the same name already exists, this command will fail.
> - `docker start` starts an existing container that was previously created with `docker run`.
>
> If you've already run LocalAI before and want to start it again, use: `docker start -i local-ai`
### CPU only image:
```bash
@@ -202,13 +193,10 @@ local-ai run oci://localai/phi-2:latest
> ⚡ **Automatic Backend Detection**: When you install models from the gallery or YAML files, LocalAI automatically detects your system's GPU capabilities (NVIDIA, AMD, Intel) and downloads the appropriate backend. For advanced configuration options, see [GPU Acceleration](https://localai.io/features/gpu-acceleration/#automatic-backend-detection).
For more information, see [💻 Getting started](https://localai.io/basics/getting_started/index.html), if you are interested in our roadmap items and future enhancements, you can see the [Issues labeled as Roadmap here](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
For more information, see [💻 Getting started](https://localai.io/basics/getting_started/index.html)
## 📰 Latest project news
- 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)
@@ -247,7 +235,7 @@ Roadmap items: [List of issues](https://github.com/mudler/LocalAI/issues?q=is%3A
- 🔍 [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)
- [Agentic capabilities](https://github.com/mudler/LocalAGI)
- 🔊 Voice activity detection (Silero-VAD support)
- 🌍 Integrated WebUI!
@@ -278,7 +266,6 @@ LocalAI supports a comprehensive range of AI backends with multiple acceleration
| **piper** | Fast neural TTS system | CPU |
| **kitten-tts** | Kitten TTS models | CPU |
| **silero-vad** | Voice Activity Detection | CPU |
| **neutts** | Text-to-speech with voice cloning | CUDA 12, ROCm, CPU |
### Image & Video Generation
| Backend | Description | Acceleration Support |
@@ -300,7 +287,7 @@ LocalAI supports a comprehensive range of AI backends with multiple acceleration
|-------------------|-------------------|------------------|
| **NVIDIA CUDA 11** | llama.cpp, whisper, stablediffusion, diffusers, rerankers, bark, chatterbox | Nvidia hardware |
| **NVIDIA CUDA 12** | All CUDA-compatible backends | Nvidia hardware |
| **AMD ROCm** | llama.cpp, whisper, vllm, transformers, diffusers, rerankers, coqui, kokoro, bark, neutts | AMD Graphics |
| **AMD ROCm** | llama.cpp, whisper, vllm, transformers, diffusers, rerankers, coqui, kokoro, bark | AMD Graphics |
| **Intel oneAPI** | llama.cpp, whisper, stablediffusion, vllm, transformers, diffusers, rfdetr, rerankers, exllama2, coqui, kokoro, bark | Intel Arc, Intel iGPUs |
| **Apple Metal** | llama.cpp, whisper, diffusers, MLX, MLX-VLM, bark-cpp | Apple M1/M2/M3+ |
| **Vulkan** | llama.cpp, whisper, stablediffusion | Cross-platform GPUs |
@@ -317,12 +304,6 @@ WebUIs:
- https://github.com/go-skynet/LocalAI-frontend
- QA-Pilot(An interactive chat project that leverages LocalAI LLMs for rapid understanding and navigation of GitHub code repository) https://github.com/reid41/QA-Pilot
Agentic Libraries:
- https://github.com/mudler/cogito
MCPs:
- https://github.com/mudler/MCPs
Model galleries
- https://github.com/go-skynet/model-gallery

View File

@@ -37,14 +37,27 @@ RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt-get update && \
apt-get install -y \
vulkan-sdk && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
software-properties-common pciutils sudo wget gpg-agent curl xz-utils && \
echo "vulkan" > /run/localai/capability && \
if [ "amd64" = "$TARGETARCH" ]; then
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt-get update && \
apt-get install -y \
vulkan-sdk && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
if [ "arm64" = "$TARGETARCH" ]; then
# For ARM64, we need to build the Vulkan SDK manually as there are no packages available
mkdir vulkan && cd vulkan && curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.321.1/vulkansdk-ubuntu-22.04-arm-1.4.321.1.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd * && \
cp -rfv aarch64/* /usr/ && \
cd ../.. && \
rm -rf vulkan
fi
fi
EOT

View File

@@ -85,14 +85,27 @@ RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt-get update && \
apt-get install -y \
vulkan-sdk && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
software-properties-common pciutils sudo wget gpg-agent curl xz-utils libxcb1 libx11-6 && \
echo "vulkan" > /run/localai/capability && \
if [ "amd64" = "$TARGETARCH" ]; then
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt-get update && \
apt-get install -y \
vulkan-sdk && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
if [ "arm64" = "$TARGETARCH" ]; then
# For ARM64, we need to build the Vulkan SDK manually as there are no packages available
mkdir vulkan && cd vulkan && curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.321.1/vulkansdk-ubuntu-22.04-arm-1.4.321.1.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd * && \
cp -rfv aarch64/* /usr/ && vulkaninfo \
cd ../.. && \
rm -rf vulkan
fi
fi
EOT
@@ -197,7 +210,7 @@ EOT
# Copy libraries using a script to handle architecture differences
RUN make -BC /LocalAI/backend/cpp/llama-cpp package
RUN make -C /LocalAI/backend/cpp/llama-cpp package
FROM scratch

View File

@@ -28,7 +28,7 @@ RUN apt-get update && \
curl python3-pip \
python-is-python3 \
python3-dev llvm \
python3-venv make cmake && \
python3-venv make && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
pip install --upgrade pip
@@ -45,14 +45,27 @@ RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt-get update && \
apt-get install -y \
vulkan-sdk && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
software-properties-common pciutils sudo wget gpg-agent curl xz-utils && \
echo "vulkan" > /run/localai/capability && \
if [ "amd64" = "$TARGETARCH" ]; then
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt-get update && \
apt-get install -y \
vulkan-sdk && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
if [ "arm64" = "$TARGETARCH" ]; then
# For ARM64, we need to build the Vulkan SDK manually as there are no packages available
mkdir vulkan && cd vulkan && curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.321.1/vulkansdk-ubuntu-22.04-arm-1.4.321.1.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd * && \
cp -rfv aarch64/* /usr/ && \
cd ../.. && \
rm -rf vulkan
fi
fi
EOT

View File

@@ -154,10 +154,6 @@ message PredictOptions {
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
@@ -168,7 +164,6 @@ message Reply {
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 {
@@ -387,11 +382,6 @@ 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 {

View File

@@ -57,7 +57,7 @@ add_library(hw_grpc_proto
${hw_proto_srcs}
${hw_proto_hdrs} )
add_executable(${TARGET} grpc-server.cpp json.hpp httplib.h)
add_executable(${TARGET} grpc-server.cpp utils.hpp json.hpp httplib.h)
target_include_directories(${TARGET} PRIVATE ../llava)
target_include_directories(${TARGET} PRIVATE ${CMAKE_SOURCE_DIR})

View File

@@ -1,5 +1,5 @@
LLAMA_VERSION?=583cb83416467e8abf9b37349dcf1f6a0083745a
LLAMA_VERSION?=4807e8f96a61b2adccebd5e57444c94d18de7264
LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
CMAKE_ARGS?=

View File

File diff suppressed because it is too large Load Diff

View File

@@ -9,13 +9,10 @@ done
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/tools/server/utils.hpp llama.cpp/tools/grpc-server/
cp -rfv llama.cpp/vendor/cpp-httplib/httplib.h llama.cpp/tools/grpc-server/
set +e

View File

@@ -8,8 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
# whisper.cpp version
WHISPER_REPO?=https://github.com/ggml-org/whisper.cpp
WHISPER_CPP_VERSION?=19ceec8eac980403b714d603e5ca31653cd42a3f
SO_TARGET?=libgowhisper.so
WHISPER_CPP_VERSION?=44fa2f647cf2a6953493b21ab83b50d5f5dbc483
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
@@ -58,18 +57,15 @@ sources/whisper.cpp:
git checkout $(WHISPER_CPP_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
# Detect OS
UNAME_S := $(shell uname -s)
libgowhisper.so: sources/whisper.cpp CMakeLists.txt gowhisper.cpp gowhisper.h
mkdir -p build && \
cd build && \
cmake .. $(CMAKE_ARGS) && \
cmake --build . --config Release -j$(JOBS) && \
cd .. && \
mv build/libgowhisper.so ./
# Only build CPU variants on Linux
ifeq ($(UNAME_S),Linux)
VARIANT_TARGETS = libgowhisper-avx.so libgowhisper-avx2.so libgowhisper-avx512.so libgowhisper-fallback.so
else
# On non-Linux (e.g., Darwin), build only fallback variant
VARIANT_TARGETS = libgowhisper-fallback.so
endif
whisper: main.go gowhisper.go $(VARIANT_TARGETS)
whisper: main.go gowhisper.go libgowhisper.so
CGO_ENABLED=0 $(GOCMD) build -tags "$(GO_TAGS)" -o whisper ./
package: whisper
@@ -77,46 +73,5 @@ package: whisper
build: package
clean: purge
rm -rf libgowhisper*.so sources/whisper.cpp whisper
purge:
rm -rf build*
# Build all variants (Linux only)
ifeq ($(UNAME_S),Linux)
libgowhisper-avx.so: sources/whisper.cpp
$(MAKE) purge
$(info ${GREEN}I whisper build info:avx${RESET})
SO_TARGET=libgowhisper-avx.so CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off" $(MAKE) libgowhisper-custom
rm -rfv build*
libgowhisper-avx2.so: sources/whisper.cpp
$(MAKE) purge
$(info ${GREEN}I whisper build info:avx2${RESET})
SO_TARGET=libgowhisper-avx2.so CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on" $(MAKE) libgowhisper-custom
rm -rfv build*
libgowhisper-avx512.so: sources/whisper.cpp
$(MAKE) purge
$(info ${GREEN}I whisper build info:avx512${RESET})
SO_TARGET=libgowhisper-avx512.so CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=on -DGGML_FMA=on -DGGML_F16C=on" $(MAKE) libgowhisper-custom
rm -rfv build*
endif
# Build fallback variant (all platforms)
libgowhisper-fallback.so: sources/whisper.cpp
$(MAKE) purge
$(info ${GREEN}I whisper build info:fallback${RESET})
SO_TARGET=libgowhisper-fallback.so CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off" $(MAKE) libgowhisper-custom
rm -rfv build*
libgowhisper-custom: CMakeLists.txt gowhisper.cpp gowhisper.h
mkdir -p build-$(SO_TARGET) && \
cd build-$(SO_TARGET) && \
cmake .. $(CMAKE_ARGS) && \
cmake --build . --config Release -j$(JOBS) && \
cd .. && \
mv build-$(SO_TARGET)/libgowhisper.so ./$(SO_TARGET)
all: whisper package
clean:
rm -rf libgowhisper.o build whisper

View File

@@ -3,7 +3,6 @@ package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
"os"
"github.com/ebitengine/purego"
grpc "github.com/mudler/LocalAI/pkg/grpc"
@@ -19,13 +18,7 @@ type LibFuncs struct {
}
func main() {
// Get library name from environment variable, default to fallback
libName := os.Getenv("WHISPER_LIBRARY")
if libName == "" {
libName = "./libgowhisper-fallback.so"
}
gosd, err := purego.Dlopen(libName, purego.RTLD_NOW|purego.RTLD_GLOBAL)
gosd, err := purego.Dlopen("./libgowhisper.so", purego.RTLD_NOW|purego.RTLD_GLOBAL)
if err != nil {
panic(err)
}

View File

@@ -10,8 +10,7 @@ CURDIR=$(dirname "$(realpath $0)")
# Create lib directory
mkdir -p $CURDIR/package/lib
cp -avf $CURDIR/whisper $CURDIR/package/
cp -fv $CURDIR/libgowhisper-*.so $CURDIR/package/
cp -avf $CURDIR/whisper $CURDIR/libgowhisper.so $CURDIR/package/
cp -fv $CURDIR/run.sh $CURDIR/package/
# Detect architecture and copy appropriate libraries

View File

@@ -1,52 +1,14 @@
#!/bin/bash
set -ex
# Get the absolute current dir where the script is located
CURDIR=$(dirname "$(realpath $0)")
cd /
echo "CPU info:"
if [ "$(uname)" != "Darwin" ]; then
grep -e "model\sname" /proc/cpuinfo | head -1
grep -e "flags" /proc/cpuinfo | head -1
fi
LIBRARY="$CURDIR/libgowhisper-fallback.so"
if [ "$(uname)" != "Darwin" ]; then
if grep -q -e "\savx\s" /proc/cpuinfo ; then
echo "CPU: AVX found OK"
if [ -e $CURDIR/libgowhisper-avx.so ]; then
LIBRARY="$CURDIR/libgowhisper-avx.so"
fi
fi
if grep -q -e "\savx2\s" /proc/cpuinfo ; then
echo "CPU: AVX2 found OK"
if [ -e $CURDIR/libgowhisper-avx2.so ]; then
LIBRARY="$CURDIR/libgowhisper-avx2.so"
fi
fi
# Check avx 512
if grep -q -e "\savx512f\s" /proc/cpuinfo ; then
echo "CPU: AVX512F found OK"
if [ -e $CURDIR/libgowhisper-avx512.so ]; then
LIBRARY="$CURDIR/libgowhisper-avx512.so"
fi
fi
fi
export LD_LIBRARY_PATH=$CURDIR/lib:$LD_LIBRARY_PATH
export WHISPER_LIBRARY=$LIBRARY
# If there is a lib/ld.so, use it
if [ -f $CURDIR/lib/ld.so ]; then
echo "Using lib/ld.so"
echo "Using library: $LIBRARY"
exec $CURDIR/lib/ld.so $CURDIR/whisper "$@"
fi
echo "Using library: $LIBRARY"
exec $CURDIR/whisper "$@"

View File

@@ -427,68 +427,6 @@
- text-to-speech
- TTS
license: apache-2.0
- &neutts
name: "neutts"
urls:
- https://github.com/neuphonic/neutts-air
description: |
NeuTTS Air is the worlds first super-realistic, on-device, TTS speech language model with instant voice cloning. Built off a 0.5B LLM backbone, NeuTTS Air brings natural-sounding speech, real-time performance, built-in security and speaker cloning to your local device - unlocking a new category of embedded voice agents, assistants, toys, and compliance-safe apps.
tags:
- text-to-speech
- TTS
license: apache-2.0
capabilities:
default: "cpu-neutts"
nvidia: "cuda12-neutts"
amd: "rocm-neutts"
nvidia-l4t: "nvidia-l4t-neutts"
- !!merge <<: *neutts
name: "neutts-development"
capabilities:
default: "cpu-neutts-development"
nvidia: "cuda12-neutts-development"
amd: "rocm-neutts-development"
nvidia-l4t: "nvidia-l4t-neutts-development"
- !!merge <<: *neutts
name: "cpu-neutts"
uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-neutts"
mirrors:
- localai/localai-backends:latest-cpu-neutts
- !!merge <<: *neutts
name: "cuda12-neutts"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-neutts"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-neutts
- !!merge <<: *neutts
name: "rocm-neutts"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-neutts"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-neutts
- !!merge <<: *neutts
name: "nvidia-l4t-neutts"
uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-arm64-neutts"
mirrors:
- localai/localai-backends:latest-nvidia-l4t-arm64-neutts
- !!merge <<: *neutts
name: "cpu-neutts-development"
uri: "quay.io/go-skynet/local-ai-backends:master-cpu-neutts"
mirrors:
- localai/localai-backends:master-cpu-neutts
- !!merge <<: *neutts
name: "cuda12-neutts-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-neutts"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-neutts
- !!merge <<: *neutts
name: "rocm-neutts-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-neutts"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-neutts
- !!merge <<: *neutts
name: "nvidia-l4t-neutts-development"
uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-arm64-neutts"
mirrors:
- localai/localai-backends:master-nvidia-l4t-arm64-neutts
- !!merge <<: *mlx
name: "mlx-development"
uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-mlx"

View File

@@ -1,4 +1,4 @@
bark==0.1.5
grpcio==1.76.0
grpcio==1.74.0
protobuf
certifi

View File

@@ -1,6 +1,6 @@
#!/usr/bin/env python3
"""
This is an extra gRPC server of LocalAI for Chatterbox TTS
This is an extra gRPC server of LocalAI for Bark TTS
"""
from concurrent import futures
import time
@@ -16,7 +16,6 @@ import torchaudio as ta
from chatterbox.tts import ChatterboxTTS
from chatterbox.mtl_tts import ChatterboxMultilingualTTS
import grpc
import tempfile
def is_float(s):
"""Check if a string can be converted to float."""
@@ -33,79 +32,11 @@ def is_int(s):
except ValueError:
return False
def split_text_at_word_boundary(text, max_length=250):
"""
Split text at word boundaries without truncating words.
Returns a list of text chunks.
"""
if not text or len(text) <= max_length:
return [text]
chunks = []
words = text.split()
current_chunk = ""
for word in words:
# Check if adding this word would exceed the limit
if len(current_chunk) + len(word) + 1 <= max_length:
if current_chunk:
current_chunk += " " + word
else:
current_chunk = word
else:
# If current chunk is not empty, add it to chunks
if current_chunk:
chunks.append(current_chunk)
current_chunk = word
else:
# If a single word is longer than max_length, we have to include it anyway
chunks.append(word)
current_chunk = ""
# Add the last chunk if it's not empty
if current_chunk:
chunks.append(current_chunk)
return chunks
def merge_audio_files(audio_files, output_path, sample_rate):
"""
Merge multiple audio files into a single audio file.
"""
if not audio_files:
return
if len(audio_files) == 1:
# If only one file, just copy it
import shutil
shutil.copy2(audio_files[0], output_path)
return
# Load all audio files
waveforms = []
for audio_file in audio_files:
waveform, sr = ta.load(audio_file)
if sr != sample_rate:
# Resample if necessary
resampler = ta.transforms.Resample(sr, sample_rate)
waveform = resampler(waveform)
waveforms.append(waveform)
# Concatenate all waveforms
merged_waveform = torch.cat(waveforms, dim=1)
# Save the merged audio
ta.save(output_path, merged_waveform, sample_rate)
# Clean up temporary files
for audio_file in audio_files:
if os.path.exists(audio_file):
os.remove(audio_file)
_ONE_DAY_IN_SECONDS = 60 * 60 * 24
# If MAX_WORKERS are specified in the environment use it, otherwise default to 1
MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))
COQUI_LANGUAGE = os.environ.get('COQUI_LANGUAGE', None)
# Implement the BackendServicer class with the service methods
class BackendServicer(backend_pb2_grpc.BackendServicer):
@@ -187,33 +118,10 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
# add options to kwargs
kwargs.update(self.options)
# Check if text exceeds 250 characters
# (chatterbox does not support long text)
# https://github.com/resemble-ai/chatterbox/issues/60
# https://github.com/resemble-ai/chatterbox/issues/110
if len(request.text) > 250:
# Split text at word boundaries
text_chunks = split_text_at_word_boundary(request.text, max_length=250)
print(f"Splitting text into chunks of 250 characters: {len(text_chunks)}", file=sys.stderr)
# Generate audio for each chunk
temp_audio_files = []
for i, chunk in enumerate(text_chunks):
# Generate audio for this chunk
wav = self.model.generate(chunk, **kwargs)
# Create temporary file for this chunk
temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.wav')
temp_file.close()
ta.save(temp_file.name, wav, self.model.sr)
temp_audio_files.append(temp_file.name)
# Merge all audio files
merge_audio_files(temp_audio_files, request.dst, self.model.sr)
else:
# Generate audio using ChatterboxTTS for short text
wav = self.model.generate(request.text, **kwargs)
# Save the generated audio
ta.save(request.dst, wav, self.model.sr)
# Generate audio using ChatterboxTTS
wav = self.model.generate(request.text, **kwargs)
# Save the generated audio
ta.save(request.dst, wav, self.model.sr)
except Exception as err:
return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")

View File

@@ -2,7 +2,6 @@
accelerate
torch
torchaudio
numpy>=1.24.0,<1.26.0
transformers
# https://github.com/mudler/LocalAI/pull/6240#issuecomment-3329518289
chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster

View File

@@ -2,7 +2,6 @@
torch==2.6.0+cu118
torchaudio==2.6.0+cu118
transformers==4.46.3
numpy>=1.24.0,<1.26.0
# https://github.com/mudler/LocalAI/pull/6240#issuecomment-3329518289
chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
accelerate

View File

@@ -1,7 +1,6 @@
torch
torchaudio
transformers
numpy>=1.24.0,<1.26.0
# https://github.com/mudler/LocalAI/pull/6240#issuecomment-3329518289
chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
accelerate

View File

@@ -2,7 +2,6 @@
torch==2.6.0+rocm6.1
torchaudio==2.6.0+rocm6.1
transformers
numpy>=1.24.0,<1.26.0
# https://github.com/mudler/LocalAI/pull/6240#issuecomment-3329518289
chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
accelerate

View File

@@ -3,7 +3,6 @@ intel-extension-for-pytorch==2.3.110+xpu
torch==2.3.1+cxx11.abi
torchaudio==2.3.1+cxx11.abi
transformers
numpy>=1.24.0,<1.26.0
# https://github.com/mudler/LocalAI/pull/6240#issuecomment-3329518289
chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
accelerate

View File

@@ -2,6 +2,5 @@
torch
torchaudio
transformers
numpy>=1.24.0,<1.26.0
chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
accelerate

View File

@@ -2,5 +2,4 @@ grpcio==1.71.0
protobuf
certifi
packaging
setuptools
poetry
setuptools

View File

@@ -1,3 +1,3 @@
grpcio==1.76.0
grpcio==1.74.0
protobuf
grpcio-tools

View File

@@ -1,4 +1,4 @@
grpcio==1.76.0
grpcio==1.74.0
protobuf
certifi
packaging==24.1

View File

@@ -1,5 +1,5 @@
setuptools
grpcio==1.76.0
grpcio==1.74.0
pillow
protobuf
certifi

View File

@@ -31,7 +31,7 @@ class TestBackendServicer(unittest.TestCase):
"""
This method tests if the server starts up successfully
"""
time.sleep(20)
time.sleep(10)
try:
self.setUp()
with grpc.insecure_channel("localhost:50051") as channel:
@@ -48,7 +48,7 @@ class TestBackendServicer(unittest.TestCase):
"""
This method tests if the model is loaded successfully
"""
time.sleep(20)
time.sleep(10)
try:
self.setUp()
with grpc.insecure_channel("localhost:50051") as channel:
@@ -66,7 +66,7 @@ class TestBackendServicer(unittest.TestCase):
"""
This method tests if the backend can generate images
"""
time.sleep(20)
time.sleep(10)
try:
self.setUp()
with grpc.insecure_channel("localhost:50051") as channel:

View File

@@ -1,4 +1,4 @@
grpcio==1.76.0
grpcio==1.74.0
protobuf
certifi
wheel

View File

@@ -64,15 +64,15 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
# Generate audio using Kokoro pipeline
generator = self.pipeline(request.text, voice=voice)
speechs = []
# Get all the audio segment
# Get the first (and typically only) audio segment
for i, (gs, ps, audio) in enumerate(generator):
speechs.append(audio)
# Save audio to the destination file
sf.write(request.dst, audio, 24000)
print(f"Generated audio segment {i}: gs={gs}, ps={ps}", file=sys.stderr)
# Merges the audio segments and writes them to the destination
speech = torch.cat(speechs, dim=0)
sf.write(request.dst, speech, 24000)
# For now, we only process the first segment
# If you need to handle multiple segments, you might want to modify this
break
except Exception as err:
return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")

View File

@@ -1,23 +0,0 @@
.PHONY: neutts
neutts:
bash install.sh
.PHONY: run
run: neutts
@echo "Running neutts..."
bash run.sh
@echo "neutts run."
.PHONY: test
test: neutts
@echo "Testing neutts..."
bash test.sh
@echo "neutts tested."
.PHONY: protogen-clean
protogen-clean:
$(RM) backend_pb2_grpc.py backend_pb2.py
.PHONY: clean
clean: protogen-clean
rm -rf venv __pycache__

View File

@@ -1,162 +0,0 @@
#!/usr/bin/env python3
"""
This is an extra gRPC server of LocalAI for NeuTTSAir
"""
from concurrent import futures
import time
import argparse
import signal
import sys
import os
import backend_pb2
import backend_pb2_grpc
import torch
from neuttsair.neutts import NeuTTSAir
import soundfile as sf
import grpc
def is_float(s):
"""Check if a string can be converted to float."""
try:
float(s)
return True
except ValueError:
return False
def is_int(s):
"""Check if a string can be converted to int."""
try:
int(s)
return True
except ValueError:
return False
_ONE_DAY_IN_SECONDS = 60 * 60 * 24
# If MAX_WORKERS are specified in the environment use it, otherwise default to 1
MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))
# Implement the BackendServicer class with the service methods
class BackendServicer(backend_pb2_grpc.BackendServicer):
"""
BackendServicer is the class that implements the gRPC service
"""
def Health(self, request, context):
return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
def LoadModel(self, request, context):
# Get device
# device = "cuda" if request.CUDA else "cpu"
if torch.cuda.is_available():
print("CUDA is available", file=sys.stderr)
device = "cuda"
else:
print("CUDA is not available", file=sys.stderr)
device = "cpu"
mps_available = hasattr(torch.backends, "mps") and torch.backends.mps.is_available()
if mps_available:
device = "mps"
if not torch.cuda.is_available() and request.CUDA:
return backend_pb2.Result(success=False, message="CUDA is not available")
options = request.Options
# empty dict
self.options = {}
self.ref_text = None
# The options are a list of strings in this form optname:optvalue
# We are storing all the options in a dict so we can use it later when
# generating the images
for opt in options:
if ":" not in opt:
continue
key, value = opt.split(":")
# if value is a number, convert it to the appropriate type
if is_float(value):
value = float(value)
elif is_int(value):
value = int(value)
elif value.lower() in ["true", "false"]:
value = value.lower() == "true"
self.options[key] = value
codec_repo = "neuphonic/neucodec"
if "codec_repo" in self.options:
codec_repo = self.options["codec_repo"]
del self.options["codec_repo"]
if "ref_text" in self.options:
self.ref_text = self.options["ref_text"]
del self.options["ref_text"]
self.AudioPath = None
if os.path.isabs(request.AudioPath):
self.AudioPath = request.AudioPath
elif request.AudioPath and request.ModelFile != "" and not os.path.isabs(request.AudioPath):
# get base path of modelFile
modelFileBase = os.path.dirname(request.ModelFile)
# modify LoraAdapter to be relative to modelFileBase
self.AudioPath = os.path.join(modelFileBase, request.AudioPath)
try:
print("Preparing models, please wait", file=sys.stderr)
self.model = NeuTTSAir(backbone_repo=request.Model, backbone_device=device, codec_repo=codec_repo, codec_device=device)
except Exception as err:
return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
# Implement your logic here for the LoadModel service
# Replace this with your desired response
return backend_pb2.Result(message="Model loaded successfully", success=True)
def TTS(self, request, context):
try:
kwargs = {}
# add options to kwargs
kwargs.update(self.options)
ref_codes = self.model.encode_reference(self.AudioPath)
wav = self.model.infer(request.text, ref_codes, self.ref_text)
sf.write(request.dst, wav, 24000)
except Exception as err:
return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
return backend_pb2.Result(success=True)
def serve(address):
server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS),
options=[
('grpc.max_message_length', 50 * 1024 * 1024), # 50MB
('grpc.max_send_message_length', 50 * 1024 * 1024), # 50MB
('grpc.max_receive_message_length', 50 * 1024 * 1024), # 50MB
])
backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
server.add_insecure_port(address)
server.start()
print("Server started. Listening on: " + address, file=sys.stderr)
# Define the signal handler function
def signal_handler(sig, frame):
print("Received termination signal. Shutting down...")
server.stop(0)
sys.exit(0)
# Set the signal handlers for SIGINT and SIGTERM
signal.signal(signal.SIGINT, signal_handler)
signal.signal(signal.SIGTERM, signal_handler)
try:
while True:
time.sleep(_ONE_DAY_IN_SECONDS)
except KeyboardInterrupt:
server.stop(0)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Run the gRPC server.")
parser.add_argument(
"--addr", default="localhost:50051", help="The address to bind the server to."
)
args = parser.parse_args()
serve(args.addr)

View File

@@ -1,33 +0,0 @@
#!/bin/bash
set -e
backend_dir=$(dirname $0)
if [ -d $backend_dir/common ]; then
source $backend_dir/common/libbackend.sh
else
source $backend_dir/../common/libbackend.sh
fi
# This is here because the Intel pip index is broken and returns 200 status codes for every package name, it just doesn't return any package links.
# This makes uv think that the package exists in the Intel pip index, and by default it stops looking at other pip indexes once it finds a match.
# We need uv to continue falling through to the pypi default index to find optimum[openvino] in the pypi index
# the --upgrade actually allows us to *downgrade* torch to the version provided in the Intel pip index
if [ "x${BUILD_PROFILE}" == "xintel" ]; then
EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
fi
if [ "x${BUILD_TYPE}" == "xcublas" ] || [ "x${BUILD_TYPE}" == "xl4t" ]; then
export CMAKE_ARGS="-DGGML_CUDA=on"
fi
if [ "x${BUILD_TYPE}" == "xhipblas" ]; then
export CMAKE_ARGS="-DGGML_HIPBLAS=on"
fi
EXTRA_PIP_INSTALL_FLAGS+=" --no-build-isolation"
git clone https://github.com/neuphonic/neutts-air neutts-air
cp -rfv neutts-air/neuttsair ./
installRequirements

View File

@@ -1,2 +0,0 @@
datasets==4.1.1
torchtune==0.6.1

View File

@@ -1,10 +0,0 @@
--extra-index-url https://download.pytorch.org/whl/cpu
accelerate
torch==2.8.0
transformers==4.56.1
librosa==0.11.0
neucodec>=0.0.4
phonemizer==3.3.0
soundfile==0.13.1
resemble-perth==1.0.1
llama-cpp-python

View File

@@ -1,8 +0,0 @@
librosa==0.11.0
neucodec>=0.0.4
phonemizer==3.3.0
soundfile==0.13.1
torch==2.8.0
transformers==4.56.1
resemble-perth==1.0.1
accelerate

View File

@@ -1,10 +0,0 @@
--extra-index-url https://download.pytorch.org/whl/rocm6.3
torch==2.8.0+rocm6.3
transformers==4.56.1
accelerate
librosa==0.11.0
neucodec>=0.0.4
phonemizer==3.3.0
soundfile==0.13.1
resemble-perth==1.0.1
llama-cpp-python

View File

@@ -1,10 +0,0 @@
--extra-index-url https://pypi.jetson-ai-lab.io/jp6/cu126/
torch
transformers
accelerate
librosa==0.11.0
neucodec>=0.0.4
phonemizer==3.3.0
soundfile==0.13.1
resemble-perth==1.0.1
llama-cpp-python

View File

@@ -1,7 +0,0 @@
grpcio==1.71.0
protobuf
certifi
packaging
setuptools
numpy==2.2.6
scikit_build_core

View File

@@ -1,10 +0,0 @@
#!/bin/bash
backend_dir=$(dirname $0)
if [ -d $backend_dir/common ]; then
source $backend_dir/common/libbackend.sh
else
source $backend_dir/../common/libbackend.sh
fi
startBackend $@

View File

@@ -1,82 +0,0 @@
"""
A test script to test the gRPC service
"""
import unittest
import subprocess
import time
import backend_pb2
import backend_pb2_grpc
import grpc
class TestBackendServicer(unittest.TestCase):
"""
TestBackendServicer is the class that tests the gRPC service
"""
def setUp(self):
"""
This method sets up the gRPC service by starting the server
"""
self.service = subprocess.Popen(["python3", "backend.py", "--addr", "localhost:50051"])
time.sleep(30)
def tearDown(self) -> None:
"""
This method tears down the gRPC service by terminating the server
"""
self.service.terminate()
self.service.wait()
def test_server_startup(self):
"""
This method tests if the server starts up successfully
"""
try:
self.setUp()
with grpc.insecure_channel("localhost:50051") as channel:
stub = backend_pb2_grpc.BackendStub(channel)
response = stub.Health(backend_pb2.HealthMessage())
self.assertEqual(response.message, b'OK')
except Exception as err:
print(err)
self.fail("Server failed to start")
finally:
self.tearDown()
def test_load_model(self):
"""
This method tests if the model is loaded successfully
"""
try:
self.setUp()
with grpc.insecure_channel("localhost:50051") as channel:
stub = backend_pb2_grpc.BackendStub(channel)
response = stub.LoadModel(backend_pb2.ModelOptions())
print(response)
self.assertTrue(response.success)
self.assertEqual(response.message, "Model loaded successfully")
except Exception as err:
print(err)
self.fail("LoadModel service failed")
finally:
self.tearDown()
def test_tts(self):
"""
This method tests if the embeddings are generated successfully
"""
try:
self.setUp()
with grpc.insecure_channel("localhost:50051") as channel:
stub = backend_pb2_grpc.BackendStub(channel)
response = stub.LoadModel(backend_pb2.ModelOptions())
self.assertTrue(response.success)
tts_request = backend_pb2.TTSRequest(text="80s TV news production music hit for tonight's biggest story")
tts_response = stub.TTS(tts_request)
self.assertIsNotNone(tts_response)
except Exception as err:
print(err)
self.fail("TTS service failed")
finally:
self.tearDown()

View File

@@ -1,11 +0,0 @@
#!/bin/bash
set -e
backend_dir=$(dirname $0)
if [ -d $backend_dir/common ]; then
source $backend_dir/common/libbackend.sh
else
source $backend_dir/../common/libbackend.sh
fi
runUnittests

View File

@@ -61,7 +61,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
if request.PipelineType != "": # Reuse the PipelineType field for language
kwargs['lang'] = request.PipelineType
self.model_name = model_name
self.model = Reranker(model_name, **kwargs)
self.model = Reranker(model_name, **kwargs)
except Exception as err:
return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
@@ -75,13 +75,12 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
documents.append(doc)
ranked_results=self.model.rank(query=request.query, docs=documents, doc_ids=list(range(len(request.documents))))
# Prepare results to return
cropped_results = ranked_results.top_k(request.top_n) if request.top_n > 0 else ranked_results
results = [
backend_pb2.DocumentResult(
index=res.doc_id,
text=res.text,
relevance_score=res.score
) for res in (cropped_results)
) for res in ranked_results.results
]
# Calculate the usage and total tokens

View File

@@ -1,3 +1,3 @@
grpcio==1.76.0
grpcio==1.74.0
protobuf
certifi

View File

@@ -76,7 +76,7 @@ class TestBackendServicer(unittest.TestCase):
)
response = stub.LoadModel(backend_pb2.ModelOptions(Model="cross-encoder"))
self.assertTrue(response.success)
rerank_response = stub.Rerank(request)
print(rerank_response.results[0])
self.assertIsNotNone(rerank_response.results)
@@ -87,60 +87,4 @@ class TestBackendServicer(unittest.TestCase):
print(err)
self.fail("Reranker service failed")
finally:
self.tearDown()
def test_rerank_omit_top_n(self):
"""
This method tests if the embeddings are generated successfully even top_n is omitted
"""
try:
self.setUp()
with grpc.insecure_channel("localhost:50051") as channel:
stub = backend_pb2_grpc.BackendStub(channel)
request = backend_pb2.RerankRequest(
query="I love you",
documents=["I hate you", "I really like you"],
top_n=0 #
)
response = stub.LoadModel(backend_pb2.ModelOptions(Model="cross-encoder"))
self.assertTrue(response.success)
rerank_response = stub.Rerank(request)
print(rerank_response.results[0])
self.assertIsNotNone(rerank_response.results)
self.assertEqual(len(rerank_response.results), 2)
self.assertEqual(rerank_response.results[0].text, "I really like you")
self.assertEqual(rerank_response.results[1].text, "I hate you")
except Exception as err:
print(err)
self.fail("Reranker service failed")
finally:
self.tearDown()
def test_rerank_crop(self):
"""
This method tests top_n cropping
"""
try:
self.setUp()
with grpc.insecure_channel("localhost:50051") as channel:
stub = backend_pb2_grpc.BackendStub(channel)
request = backend_pb2.RerankRequest(
query="I love you",
documents=["I hate you", "I really like you", "I hate ignoring top_n"],
top_n=2
)
response = stub.LoadModel(backend_pb2.ModelOptions(Model="cross-encoder"))
self.assertTrue(response.success)
rerank_response = stub.Rerank(request)
print(rerank_response.results[0])
self.assertIsNotNone(rerank_response.results)
self.assertEqual(len(rerank_response.results), 2)
self.assertEqual(rerank_response.results[0].text, "I really like you")
self.assertEqual(rerank_response.results[1].text, "I hate you")
except Exception as err:
print(err)
self.fail("Reranker service failed")
finally:
self.tearDown()
self.tearDown()

View File

@@ -6,4 +6,4 @@ transformers
bitsandbytes
outetts
sentence-transformers==5.1.0
protobuf==6.33.1
protobuf==6.32.0

View File

@@ -7,4 +7,4 @@ transformers
bitsandbytes
outetts
sentence-transformers==5.1.0
protobuf==6.33.1
protobuf==6.32.0

View File

@@ -6,4 +6,4 @@ transformers
bitsandbytes
outetts
sentence-transformers==5.1.0
protobuf==6.33.1
protobuf==6.32.0

View File

@@ -8,4 +8,4 @@ bitsandbytes
outetts
bitsandbytes
sentence-transformers==5.1.0
protobuf==6.33.1
protobuf==6.32.0

View File

@@ -10,4 +10,4 @@ intel-extension-for-transformers
bitsandbytes
outetts
sentence-transformers==5.1.0
protobuf==6.33.1
protobuf==6.32.0

View File

@@ -1,5 +1,5 @@
grpcio==1.76.0
protobuf==6.33.1
grpcio==1.75.0
protobuf==6.32.0
certifi
setuptools
scipy==1.15.1

View File

@@ -3,13 +3,6 @@ set -e
EXTRA_PIP_INSTALL_FLAGS="--no-build-isolation"
# Avoid to overcommit the CPU during build
# https://github.com/vllm-project/vllm/issues/20079
# https://docs.vllm.ai/en/v0.8.3/serving/env_vars.html
# https://docs.redhat.com/it/documentation/red_hat_ai_inference_server/3.0/html/vllm_server_arguments/environment_variables-server-arguments
export NVCC_THREADS=2
export MAX_JOBS=1
backend_dir=$(dirname $0)
if [ -d $backend_dir/common ]; then

View File

@@ -1 +1 @@
https://github.com/Dao-AILab/flash-attention/releases/download/v2.8.3/flash_attn-2.8.3+cu12torch2.7cxx11abiTRUE-cp310-cp310-linux_x86_64.whl
flash-attn

View File

@@ -1,4 +1,4 @@
grpcio==1.76.0
grpcio==1.74.0
protobuf
certifi
setuptools

View File

@@ -2,12 +2,14 @@ package main
import (
"log"
"os"
"os/signal"
"syscall"
"fyne.io/fyne/v2"
"fyne.io/fyne/v2/app"
"fyne.io/fyne/v2/driver/desktop"
coreLauncher "github.com/mudler/LocalAI/cmd/launcher/internal"
"github.com/mudler/LocalAI/pkg/signals"
)
func main() {
@@ -40,12 +42,7 @@ func main() {
}
// Setup signal handling for graceful shutdown
signals.RegisterGracefulTerminationHandler(func() {
// Perform cleanup
if err := launcher.Shutdown(); err != nil {
log.Printf("Error during shutdown: %v", err)
}
})
setupSignalHandling(launcher)
// Initialize the launcher state
go func() {
@@ -70,3 +67,26 @@ func main() {
// Run the application in background (window only shown when "Settings" is clicked)
myApp.Run()
}
// setupSignalHandling sets up signal handlers for graceful shutdown
func setupSignalHandling(launcher *coreLauncher.Launcher) {
// Create a channel to receive OS signals
sigChan := make(chan os.Signal, 1)
// Register for interrupt and terminate signals
signal.Notify(sigChan, syscall.SIGINT, syscall.SIGTERM)
// Handle signals in a separate goroutine
go func() {
sig := <-sigChan
log.Printf("Received signal %v, shutting down gracefully...", sig)
// Perform cleanup
if err := launcher.Shutdown(); err != nil {
log.Printf("Error during shutdown: %v", err)
}
// Exit the application
os.Exit(0)
}()
}

View File

@@ -1,9 +1,6 @@
package application
import (
"context"
"sync"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/services"
"github.com/mudler/LocalAI/core/templates"
@@ -14,14 +11,8 @@ type Application struct {
backendLoader *config.ModelConfigLoader
modelLoader *model.ModelLoader
applicationConfig *config.ApplicationConfig
startupConfig *config.ApplicationConfig // Stores original config from env vars (before file loading)
templatesEvaluator *templates.Evaluator
galleryService *services.GalleryService
watchdogMutex sync.Mutex
watchdogStop chan bool
p2pMutex sync.Mutex
p2pCtx context.Context
p2pCancel context.CancelFunc
}
func newApplication(appConfig *config.ApplicationConfig) *Application {
@@ -53,11 +44,6 @@ func (a *Application) GalleryService() *services.GalleryService {
return a.galleryService
}
// StartupConfig returns the original startup configuration (from env vars, before file loading)
func (a *Application) StartupConfig() *config.ApplicationConfig {
return a.startupConfig
}
func (a *Application) start() error {
galleryService := services.NewGalleryService(a.ApplicationConfig(), a.ModelLoader())
err := galleryService.Start(a.ApplicationConfig().Context, a.ModelConfigLoader(), a.ApplicationConfig().SystemState)

View File

@@ -1,343 +1,180 @@
package application
import (
"encoding/json"
"fmt"
"os"
"path"
"path/filepath"
"time"
"dario.cat/mergo"
"github.com/fsnotify/fsnotify"
"github.com/mudler/LocalAI/core/config"
"github.com/rs/zerolog/log"
)
type fileHandler func(fileContent []byte, appConfig *config.ApplicationConfig) error
type configFileHandler struct {
handlers map[string]fileHandler
watcher *fsnotify.Watcher
appConfig *config.ApplicationConfig
}
// TODO: This should be a singleton eventually so other parts of the code can register config file handlers,
// then we can export it to other packages
func newConfigFileHandler(appConfig *config.ApplicationConfig) configFileHandler {
c := configFileHandler{
handlers: make(map[string]fileHandler),
appConfig: appConfig,
}
err := c.Register("api_keys.json", readApiKeysJson(*appConfig), true)
if err != nil {
log.Error().Err(err).Str("file", "api_keys.json").Msg("unable to register config file handler")
}
err = c.Register("external_backends.json", readExternalBackendsJson(*appConfig), true)
if err != nil {
log.Error().Err(err).Str("file", "external_backends.json").Msg("unable to register config file handler")
}
err = c.Register("runtime_settings.json", readRuntimeSettingsJson(*appConfig), true)
if err != nil {
log.Error().Err(err).Str("file", "runtime_settings.json").Msg("unable to register config file handler")
}
return c
}
func (c *configFileHandler) Register(filename string, handler fileHandler, runNow bool) error {
_, ok := c.handlers[filename]
if ok {
return fmt.Errorf("handler already registered for file %s", filename)
}
c.handlers[filename] = handler
if runNow {
c.callHandler(filename, handler)
}
return nil
}
func (c *configFileHandler) callHandler(filename string, handler fileHandler) {
rootedFilePath := filepath.Join(c.appConfig.DynamicConfigsDir, filepath.Clean(filename))
log.Trace().Str("filename", rootedFilePath).Msg("reading file for dynamic config update")
fileContent, err := os.ReadFile(rootedFilePath)
if err != nil && !os.IsNotExist(err) {
log.Error().Err(err).Str("filename", rootedFilePath).Msg("could not read file")
}
if err = handler(fileContent, c.appConfig); err != nil {
log.Error().Err(err).Msg("WatchConfigDirectory goroutine failed to update options")
}
}
func (c *configFileHandler) Watch() error {
configWatcher, err := fsnotify.NewWatcher()
c.watcher = configWatcher
if err != nil {
return err
}
if c.appConfig.DynamicConfigsDirPollInterval > 0 {
log.Debug().Msg("Poll interval set, falling back to polling for configuration changes")
ticker := time.NewTicker(c.appConfig.DynamicConfigsDirPollInterval)
go func() {
for {
<-ticker.C
for file, handler := range c.handlers {
log.Debug().Str("file", file).Msg("polling config file")
c.callHandler(file, handler)
}
}
}()
}
// Start listening for events.
go func() {
for {
select {
case event, ok := <-c.watcher.Events:
if !ok {
return
}
if event.Has(fsnotify.Write | fsnotify.Create | fsnotify.Remove) {
handler, ok := c.handlers[path.Base(event.Name)]
if !ok {
continue
}
c.callHandler(filepath.Base(event.Name), handler)
}
case err, ok := <-c.watcher.Errors:
log.Error().Err(err).Msg("config watcher error received")
if !ok {
return
}
}
}
}()
// Add a path.
err = c.watcher.Add(c.appConfig.DynamicConfigsDir)
if err != nil {
return fmt.Errorf("unable to create a watcher on the configuration directory: %+v", err)
}
return nil
}
// TODO: When we institute graceful shutdown, this should be called
func (c *configFileHandler) Stop() error {
return c.watcher.Close()
}
func readApiKeysJson(startupAppConfig config.ApplicationConfig) fileHandler {
handler := func(fileContent []byte, appConfig *config.ApplicationConfig) error {
log.Debug().Msg("processing api keys runtime update")
log.Trace().Int("numKeys", len(startupAppConfig.ApiKeys)).Msg("api keys provided at startup")
if len(fileContent) > 0 {
// Parse JSON content from the file
var fileKeys []string
err := json.Unmarshal(fileContent, &fileKeys)
if err != nil {
return err
}
log.Trace().Int("numKeys", len(fileKeys)).Msg("discovered API keys from api keys dynamic config dile")
appConfig.ApiKeys = append(startupAppConfig.ApiKeys, fileKeys...)
} else {
log.Trace().Msg("no API keys discovered from dynamic config file")
appConfig.ApiKeys = startupAppConfig.ApiKeys
}
log.Trace().Int("numKeys", len(appConfig.ApiKeys)).Msg("total api keys after processing")
return nil
}
return handler
}
func readExternalBackendsJson(startupAppConfig config.ApplicationConfig) fileHandler {
handler := func(fileContent []byte, appConfig *config.ApplicationConfig) error {
log.Debug().Msg("processing external_backends.json")
if len(fileContent) > 0 {
// Parse JSON content from the file
var fileBackends map[string]string
err := json.Unmarshal(fileContent, &fileBackends)
if err != nil {
return err
}
appConfig.ExternalGRPCBackends = startupAppConfig.ExternalGRPCBackends
err = mergo.Merge(&appConfig.ExternalGRPCBackends, &fileBackends)
if err != nil {
return err
}
} else {
appConfig.ExternalGRPCBackends = startupAppConfig.ExternalGRPCBackends
}
log.Debug().Msg("external backends loaded from external_backends.json")
return nil
}
return handler
}
type runtimeSettings struct {
WatchdogEnabled *bool `json:"watchdog_enabled,omitempty"`
WatchdogIdleEnabled *bool `json:"watchdog_idle_enabled,omitempty"`
WatchdogBusyEnabled *bool `json:"watchdog_busy_enabled,omitempty"`
WatchdogIdleTimeout *string `json:"watchdog_idle_timeout,omitempty"`
WatchdogBusyTimeout *string `json:"watchdog_busy_timeout,omitempty"`
SingleBackend *bool `json:"single_backend,omitempty"`
ParallelBackendRequests *bool `json:"parallel_backend_requests,omitempty"`
Threads *int `json:"threads,omitempty"`
ContextSize *int `json:"context_size,omitempty"`
F16 *bool `json:"f16,omitempty"`
Debug *bool `json:"debug,omitempty"`
CORS *bool `json:"cors,omitempty"`
CSRF *bool `json:"csrf,omitempty"`
CORSAllowOrigins *string `json:"cors_allow_origins,omitempty"`
P2PToken *string `json:"p2p_token,omitempty"`
P2PNetworkID *string `json:"p2p_network_id,omitempty"`
Federated *bool `json:"federated,omitempty"`
Galleries *[]config.Gallery `json:"galleries,omitempty"`
BackendGalleries *[]config.Gallery `json:"backend_galleries,omitempty"`
AutoloadGalleries *bool `json:"autoload_galleries,omitempty"`
AutoloadBackendGalleries *bool `json:"autoload_backend_galleries,omitempty"`
ApiKeys *[]string `json:"api_keys,omitempty"`
}
func readRuntimeSettingsJson(startupAppConfig config.ApplicationConfig) fileHandler {
handler := func(fileContent []byte, appConfig *config.ApplicationConfig) error {
log.Debug().Msg("processing runtime_settings.json")
// Determine if settings came from env vars by comparing with startup config
// startupAppConfig contains the original values set from env vars at startup.
// If current values match startup values, they came from env vars (or defaults).
// We apply file settings only if current values match startup values (meaning not from env vars).
envWatchdogIdle := appConfig.WatchDogIdle == startupAppConfig.WatchDogIdle
envWatchdogBusy := appConfig.WatchDogBusy == startupAppConfig.WatchDogBusy
envWatchdogIdleTimeout := appConfig.WatchDogIdleTimeout == startupAppConfig.WatchDogIdleTimeout
envWatchdogBusyTimeout := appConfig.WatchDogBusyTimeout == startupAppConfig.WatchDogBusyTimeout
envSingleBackend := appConfig.SingleBackend == startupAppConfig.SingleBackend
envParallelRequests := appConfig.ParallelBackendRequests == startupAppConfig.ParallelBackendRequests
envThreads := appConfig.Threads == startupAppConfig.Threads
envContextSize := appConfig.ContextSize == startupAppConfig.ContextSize
envF16 := appConfig.F16 == startupAppConfig.F16
envDebug := appConfig.Debug == startupAppConfig.Debug
envCORS := appConfig.CORS == startupAppConfig.CORS
envCSRF := appConfig.CSRF == startupAppConfig.CSRF
envCORSAllowOrigins := appConfig.CORSAllowOrigins == startupAppConfig.CORSAllowOrigins
envP2PToken := appConfig.P2PToken == startupAppConfig.P2PToken
envP2PNetworkID := appConfig.P2PNetworkID == startupAppConfig.P2PNetworkID
envFederated := appConfig.Federated == startupAppConfig.Federated
envAutoloadGalleries := appConfig.AutoloadGalleries == startupAppConfig.AutoloadGalleries
envAutoloadBackendGalleries := appConfig.AutoloadBackendGalleries == startupAppConfig.AutoloadBackendGalleries
if len(fileContent) > 0 {
var settings runtimeSettings
err := json.Unmarshal(fileContent, &settings)
if err != nil {
return err
}
// Apply file settings only if they don't match startup values (i.e., not from env vars)
if settings.WatchdogIdleEnabled != nil && !envWatchdogIdle {
appConfig.WatchDogIdle = *settings.WatchdogIdleEnabled
if appConfig.WatchDogIdle {
appConfig.WatchDog = true
}
}
if settings.WatchdogBusyEnabled != nil && !envWatchdogBusy {
appConfig.WatchDogBusy = *settings.WatchdogBusyEnabled
if appConfig.WatchDogBusy {
appConfig.WatchDog = true
}
}
if settings.WatchdogIdleTimeout != nil && !envWatchdogIdleTimeout {
dur, err := time.ParseDuration(*settings.WatchdogIdleTimeout)
if err == nil {
appConfig.WatchDogIdleTimeout = dur
} else {
log.Warn().Err(err).Str("timeout", *settings.WatchdogIdleTimeout).Msg("invalid watchdog idle timeout in runtime_settings.json")
}
}
if settings.WatchdogBusyTimeout != nil && !envWatchdogBusyTimeout {
dur, err := time.ParseDuration(*settings.WatchdogBusyTimeout)
if err == nil {
appConfig.WatchDogBusyTimeout = dur
} else {
log.Warn().Err(err).Str("timeout", *settings.WatchdogBusyTimeout).Msg("invalid watchdog busy timeout in runtime_settings.json")
}
}
if settings.SingleBackend != nil && !envSingleBackend {
appConfig.SingleBackend = *settings.SingleBackend
}
if settings.ParallelBackendRequests != nil && !envParallelRequests {
appConfig.ParallelBackendRequests = *settings.ParallelBackendRequests
}
if settings.Threads != nil && !envThreads {
appConfig.Threads = *settings.Threads
}
if settings.ContextSize != nil && !envContextSize {
appConfig.ContextSize = *settings.ContextSize
}
if settings.F16 != nil && !envF16 {
appConfig.F16 = *settings.F16
}
if settings.Debug != nil && !envDebug {
appConfig.Debug = *settings.Debug
}
if settings.CORS != nil && !envCORS {
appConfig.CORS = *settings.CORS
}
if settings.CSRF != nil && !envCSRF {
appConfig.CSRF = *settings.CSRF
}
if settings.CORSAllowOrigins != nil && !envCORSAllowOrigins {
appConfig.CORSAllowOrigins = *settings.CORSAllowOrigins
}
if settings.P2PToken != nil && !envP2PToken {
appConfig.P2PToken = *settings.P2PToken
}
if settings.P2PNetworkID != nil && !envP2PNetworkID {
appConfig.P2PNetworkID = *settings.P2PNetworkID
}
if settings.Federated != nil && !envFederated {
appConfig.Federated = *settings.Federated
}
if settings.Galleries != nil {
appConfig.Galleries = *settings.Galleries
}
if settings.BackendGalleries != nil {
appConfig.BackendGalleries = *settings.BackendGalleries
}
if settings.AutoloadGalleries != nil && !envAutoloadGalleries {
appConfig.AutoloadGalleries = *settings.AutoloadGalleries
}
if settings.AutoloadBackendGalleries != nil && !envAutoloadBackendGalleries {
appConfig.AutoloadBackendGalleries = *settings.AutoloadBackendGalleries
}
if settings.ApiKeys != nil {
// API keys from env vars (startup) should be kept, runtime settings keys replace all runtime keys
// If runtime_settings.json specifies ApiKeys (even if empty), it replaces all runtime keys
// Start with env keys, then add runtime_settings.json keys (which may be empty to clear them)
envKeys := startupAppConfig.ApiKeys
runtimeKeys := *settings.ApiKeys
// Replace all runtime keys with what's in runtime_settings.json
appConfig.ApiKeys = append(envKeys, runtimeKeys...)
}
// If watchdog is enabled via file but not via env, ensure WatchDog flag is set
if !envWatchdogIdle && !envWatchdogBusy {
if settings.WatchdogEnabled != nil && *settings.WatchdogEnabled {
appConfig.WatchDog = true
}
}
}
log.Debug().Msg("runtime settings loaded from runtime_settings.json")
return nil
}
return handler
}
package application
import (
"encoding/json"
"fmt"
"os"
"path"
"path/filepath"
"time"
"dario.cat/mergo"
"github.com/fsnotify/fsnotify"
"github.com/mudler/LocalAI/core/config"
"github.com/rs/zerolog/log"
)
type fileHandler func(fileContent []byte, appConfig *config.ApplicationConfig) error
type configFileHandler struct {
handlers map[string]fileHandler
watcher *fsnotify.Watcher
appConfig *config.ApplicationConfig
}
// TODO: This should be a singleton eventually so other parts of the code can register config file handlers,
// then we can export it to other packages
func newConfigFileHandler(appConfig *config.ApplicationConfig) configFileHandler {
c := configFileHandler{
handlers: make(map[string]fileHandler),
appConfig: appConfig,
}
err := c.Register("api_keys.json", readApiKeysJson(*appConfig), true)
if err != nil {
log.Error().Err(err).Str("file", "api_keys.json").Msg("unable to register config file handler")
}
err = c.Register("external_backends.json", readExternalBackendsJson(*appConfig), true)
if err != nil {
log.Error().Err(err).Str("file", "external_backends.json").Msg("unable to register config file handler")
}
return c
}
func (c *configFileHandler) Register(filename string, handler fileHandler, runNow bool) error {
_, ok := c.handlers[filename]
if ok {
return fmt.Errorf("handler already registered for file %s", filename)
}
c.handlers[filename] = handler
if runNow {
c.callHandler(filename, handler)
}
return nil
}
func (c *configFileHandler) callHandler(filename string, handler fileHandler) {
rootedFilePath := filepath.Join(c.appConfig.DynamicConfigsDir, filepath.Clean(filename))
log.Trace().Str("filename", rootedFilePath).Msg("reading file for dynamic config update")
fileContent, err := os.ReadFile(rootedFilePath)
if err != nil && !os.IsNotExist(err) {
log.Error().Err(err).Str("filename", rootedFilePath).Msg("could not read file")
}
if err = handler(fileContent, c.appConfig); err != nil {
log.Error().Err(err).Msg("WatchConfigDirectory goroutine failed to update options")
}
}
func (c *configFileHandler) Watch() error {
configWatcher, err := fsnotify.NewWatcher()
c.watcher = configWatcher
if err != nil {
return err
}
if c.appConfig.DynamicConfigsDirPollInterval > 0 {
log.Debug().Msg("Poll interval set, falling back to polling for configuration changes")
ticker := time.NewTicker(c.appConfig.DynamicConfigsDirPollInterval)
go func() {
for {
<-ticker.C
for file, handler := range c.handlers {
log.Debug().Str("file", file).Msg("polling config file")
c.callHandler(file, handler)
}
}
}()
}
// Start listening for events.
go func() {
for {
select {
case event, ok := <-c.watcher.Events:
if !ok {
return
}
if event.Has(fsnotify.Write | fsnotify.Create | fsnotify.Remove) {
handler, ok := c.handlers[path.Base(event.Name)]
if !ok {
continue
}
c.callHandler(filepath.Base(event.Name), handler)
}
case err, ok := <-c.watcher.Errors:
log.Error().Err(err).Msg("config watcher error received")
if !ok {
return
}
}
}
}()
// Add a path.
err = c.watcher.Add(c.appConfig.DynamicConfigsDir)
if err != nil {
return fmt.Errorf("unable to create a watcher on the configuration directory: %+v", err)
}
return nil
}
// TODO: When we institute graceful shutdown, this should be called
func (c *configFileHandler) Stop() error {
return c.watcher.Close()
}
func readApiKeysJson(startupAppConfig config.ApplicationConfig) fileHandler {
handler := func(fileContent []byte, appConfig *config.ApplicationConfig) error {
log.Debug().Msg("processing api keys runtime update")
log.Trace().Int("numKeys", len(startupAppConfig.ApiKeys)).Msg("api keys provided at startup")
if len(fileContent) > 0 {
// Parse JSON content from the file
var fileKeys []string
err := json.Unmarshal(fileContent, &fileKeys)
if err != nil {
return err
}
log.Trace().Int("numKeys", len(fileKeys)).Msg("discovered API keys from api keys dynamic config dile")
appConfig.ApiKeys = append(startupAppConfig.ApiKeys, fileKeys...)
} else {
log.Trace().Msg("no API keys discovered from dynamic config file")
appConfig.ApiKeys = startupAppConfig.ApiKeys
}
log.Trace().Int("numKeys", len(appConfig.ApiKeys)).Msg("total api keys after processing")
return nil
}
return handler
}
func readExternalBackendsJson(startupAppConfig config.ApplicationConfig) fileHandler {
handler := func(fileContent []byte, appConfig *config.ApplicationConfig) error {
log.Debug().Msg("processing external_backends.json")
if len(fileContent) > 0 {
// Parse JSON content from the file
var fileBackends map[string]string
err := json.Unmarshal(fileContent, &fileBackends)
if err != nil {
return err
}
appConfig.ExternalGRPCBackends = startupAppConfig.ExternalGRPCBackends
err = mergo.Merge(&appConfig.ExternalGRPCBackends, &fileBackends)
if err != nil {
return err
}
} else {
appConfig.ExternalGRPCBackends = startupAppConfig.ExternalGRPCBackends
}
log.Debug().Msg("external backends loaded from external_backends.json")
return nil
}
return handler
}

View File

@@ -1,240 +0,0 @@
package application
import (
"context"
"fmt"
"net"
"slices"
"time"
"github.com/google/uuid"
"github.com/mudler/LocalAI/core/gallery"
"github.com/mudler/LocalAI/core/p2p"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services"
"github.com/mudler/edgevpn/pkg/node"
"github.com/rs/zerolog/log"
zlog "github.com/rs/zerolog/log"
)
func (a *Application) StopP2P() error {
if a.p2pCancel != nil {
a.p2pCancel()
a.p2pCancel = nil
a.p2pCtx = nil
// Wait a bit for shutdown to complete
time.Sleep(200 * time.Millisecond)
}
return nil
}
func (a *Application) StartP2P() error {
// we need a p2p token
if a.applicationConfig.P2PToken == "" {
return fmt.Errorf("P2P token is not set")
}
networkID := a.applicationConfig.P2PNetworkID
ctx, cancel := context.WithCancel(a.ApplicationConfig().Context)
a.p2pCtx = ctx
a.p2pCancel = cancel
var n *node.Node
// Here we are avoiding creating multiple nodes:
// - if the federated mode is enabled, we create a federated node and expose a service
// - exposing a service creates a node with specific options, and we don't want to create another node
// If the federated mode is enabled, we expose a service to the local instance running
// at r.Address
if a.applicationConfig.Federated {
_, port, err := net.SplitHostPort(a.applicationConfig.APIAddress)
if err != nil {
return err
}
// Here a new node is created and started
// and a service is exposed by the node
node, err := p2p.ExposeService(ctx, "localhost", port, a.applicationConfig.P2PToken, p2p.NetworkID(networkID, p2p.FederatedID))
if err != nil {
return err
}
if err := p2p.ServiceDiscoverer(ctx, node, a.applicationConfig.P2PToken, p2p.NetworkID(networkID, p2p.FederatedID), nil, false); err != nil {
return err
}
n = node
// start node sync in the background
if err := a.p2pSync(ctx, node); err != nil {
return err
}
}
// If a node wasn't created previously, create it
if n == nil {
node, err := p2p.NewNode(a.applicationConfig.P2PToken)
if err != nil {
return err
}
err = node.Start(ctx)
if err != nil {
return fmt.Errorf("starting new node: %w", err)
}
n = node
}
// Attach a ServiceDiscoverer to the p2p node
log.Info().Msg("Starting P2P server discovery...")
if err := p2p.ServiceDiscoverer(ctx, n, a.applicationConfig.P2PToken, p2p.NetworkID(networkID, p2p.WorkerID), func(serviceID string, node schema.NodeData) {
var tunnelAddresses []string
for _, v := range p2p.GetAvailableNodes(p2p.NetworkID(networkID, p2p.WorkerID)) {
if v.IsOnline() {
tunnelAddresses = append(tunnelAddresses, v.TunnelAddress)
} else {
log.Info().Msgf("Node %s is offline", v.ID)
}
}
if a.applicationConfig.TunnelCallback != nil {
a.applicationConfig.TunnelCallback(tunnelAddresses)
}
}, true); err != nil {
return err
}
return nil
}
// RestartP2P restarts the P2P stack with current ApplicationConfig settings
// Note: This method signals that P2P should be restarted, but the actual restart
// is handled by the caller to avoid import cycles
func (a *Application) RestartP2P() error {
a.p2pMutex.Lock()
defer a.p2pMutex.Unlock()
// Stop existing P2P if running
if a.p2pCancel != nil {
a.p2pCancel()
a.p2pCancel = nil
a.p2pCtx = nil
// Wait a bit for shutdown to complete
time.Sleep(200 * time.Millisecond)
}
appConfig := a.ApplicationConfig()
// Start P2P if token is set
if appConfig.P2PToken == "" {
return fmt.Errorf("P2P token is not set")
}
// Create new context for P2P
ctx, cancel := context.WithCancel(appConfig.Context)
a.p2pCtx = ctx
a.p2pCancel = cancel
// Get API address from config
address := appConfig.APIAddress
if address == "" {
address = "127.0.0.1:8080" // default
}
// Start P2P stack in a goroutine
go func() {
if err := a.StartP2P(); err != nil {
log.Error().Err(err).Msg("Failed to start P2P stack")
cancel() // Cancel context on error
}
}()
log.Info().Msg("P2P stack restarted with new settings")
return nil
}
func syncState(ctx context.Context, n *node.Node, app *Application) error {
zlog.Debug().Msg("[p2p-sync] Syncing state")
whatWeHave := []string{}
for _, model := range app.ModelConfigLoader().GetAllModelsConfigs() {
whatWeHave = append(whatWeHave, model.Name)
}
ledger, _ := n.Ledger()
currentData := ledger.CurrentData()
zlog.Debug().Msgf("[p2p-sync] Current data: %v", currentData)
data, exists := ledger.GetKey("shared_state", "models")
if !exists {
ledger.AnnounceUpdate(ctx, time.Minute, "shared_state", "models", whatWeHave)
zlog.Debug().Msgf("No models found in the ledger, announced our models: %v", whatWeHave)
}
models := []string{}
if err := data.Unmarshal(&models); err != nil {
zlog.Warn().Err(err).Msg("error unmarshalling models")
return nil
}
zlog.Debug().Msgf("[p2p-sync] Models that are present in this instance: %v\nModels that are in the ledger: %v", whatWeHave, models)
// Sync with our state
whatIsNotThere := []string{}
for _, model := range whatWeHave {
if !slices.Contains(models, model) {
whatIsNotThere = append(whatIsNotThere, model)
}
}
if len(whatIsNotThere) > 0 {
zlog.Debug().Msgf("[p2p-sync] Announcing our models: %v", append(models, whatIsNotThere...))
ledger.AnnounceUpdate(
ctx,
1*time.Minute,
"shared_state",
"models",
append(models, whatIsNotThere...),
)
}
// Check if we have a model that is not in our state, otherwise install it
for _, model := range models {
if slices.Contains(whatWeHave, model) {
zlog.Debug().Msgf("[p2p-sync] Model %s is already present in this instance", model)
continue
}
// we install model
zlog.Info().Msgf("[p2p-sync] Installing model which is not present in this instance: %s", model)
uuid, err := uuid.NewUUID()
if err != nil {
zlog.Error().Err(err).Msg("error generating UUID")
continue
}
app.GalleryService().ModelGalleryChannel <- services.GalleryOp[gallery.GalleryModel, gallery.ModelConfig]{
ID: uuid.String(),
GalleryElementName: model,
Galleries: app.ApplicationConfig().Galleries,
BackendGalleries: app.ApplicationConfig().BackendGalleries,
}
}
return nil
}
func (a *Application) p2pSync(ctx context.Context, n *node.Node) error {
go func() {
for {
select {
case <-ctx.Done():
return
case <-time.After(1 * time.Minute):
if err := syncState(ctx, n, a); err != nil {
zlog.Error().Err(err).Msg("error syncing state")
}
}
}
}()
return nil
}

View File

@@ -1,11 +1,8 @@
package application
import (
"encoding/json"
"fmt"
"os"
"path/filepath"
"time"
"github.com/mudler/LocalAI/core/backend"
"github.com/mudler/LocalAI/core/config"
@@ -21,24 +18,13 @@ import (
func New(opts ...config.AppOption) (*Application, error) {
options := config.NewApplicationConfig(opts...)
// Store a copy of the startup config (from env vars, before file loading)
// This is used to determine if settings came from env vars vs file
startupConfigCopy := *options
application := newApplication(options)
application.startupConfig = &startupConfigCopy
log.Info().Msgf("Starting LocalAI using %d threads, with models path: %s", options.Threads, options.SystemState.Model.ModelsPath)
log.Info().Msgf("LocalAI version: %s", internal.PrintableVersion())
if err := application.start(); err != nil {
return nil, err
}
caps, err := xsysinfo.CPUCapabilities()
if err == nil {
log.Debug().Msgf("CPU capabilities: %v", caps)
}
gpus, err := xsysinfo.GPUs()
if err == nil {
@@ -70,12 +56,12 @@ func New(opts ...config.AppOption) (*Application, error) {
}
}
if err := coreStartup.InstallModels(options.Context, application.GalleryService(), options.Galleries, options.BackendGalleries, options.SystemState, application.ModelLoader(), options.EnforcePredownloadScans, options.AutoloadBackendGalleries, nil, options.ModelsURL...); err != nil {
if err := coreStartup.InstallModels(options.Galleries, options.BackendGalleries, options.SystemState, application.ModelLoader(), options.EnforcePredownloadScans, options.AutoloadBackendGalleries, nil, options.ModelsURL...); err != nil {
log.Error().Err(err).Msg("error installing models")
}
for _, backend := range options.ExternalBackends {
if err := coreStartup.InstallExternalBackends(options.Context, options.BackendGalleries, options.SystemState, application.ModelLoader(), nil, backend, "", ""); err != nil {
if err := coreStartup.InstallExternalBackends(options.BackendGalleries, options.SystemState, application.ModelLoader(), nil, backend, "", ""); err != nil {
log.Error().Err(err).Msg("error installing external backend")
}
}
@@ -118,13 +104,6 @@ func New(opts ...config.AppOption) (*Application, error) {
}
}
// Load runtime settings from file if DynamicConfigsDir is set
// This applies file settings with env var precedence (env vars take priority)
// Note: startupConfigCopy was already created above, so it has the original env var values
if options.DynamicConfigsDir != "" {
loadRuntimeSettingsFromFile(options)
}
// turn off any process that was started by GRPC if the context is canceled
go func() {
<-options.Context.Done()
@@ -135,8 +114,21 @@ func New(opts ...config.AppOption) (*Application, error) {
}
}()
// Initialize watchdog with current settings (after loading from file)
initializeWatchdog(application, options)
if options.WatchDog {
wd := model.NewWatchDog(
application.ModelLoader(),
options.WatchDogBusyTimeout,
options.WatchDogIdleTimeout,
options.WatchDogBusy,
options.WatchDogIdle)
application.ModelLoader().SetWatchDog(wd)
go wd.Run()
go func() {
<-options.Context.Done()
log.Debug().Msgf("Context canceled, shutting down")
wd.Shutdown()
}()
}
if options.LoadToMemory != nil && !options.SingleBackend {
for _, m := range options.LoadToMemory {
@@ -160,6 +152,10 @@ func New(opts ...config.AppOption) (*Application, error) {
// Watch the configuration directory
startWatcher(options)
if err := application.start(); err != nil {
return nil, err
}
log.Info().Msg("core/startup process completed!")
return application, nil
}
@@ -188,131 +184,3 @@ func startWatcher(options *config.ApplicationConfig) {
log.Error().Err(err).Msg("failed creating watcher")
}
}
// loadRuntimeSettingsFromFile loads settings from runtime_settings.json with env var precedence
// This function is called at startup, before env vars are applied via AppOptions.
// Since env vars are applied via AppOptions in run.go, we need to check if they're set.
// We do this by checking if the current options values differ from defaults, which would
// indicate they were set from env vars. However, a simpler approach is to just apply
// file settings here, and let the AppOptions (which are applied after this) override them.
// But actually, this is called AFTER AppOptions are applied in New(), so we need to check env vars.
// The cleanest solution: Store original values before applying file, or check if values match
// what would be set from env vars. For now, we'll apply file settings and they'll be
// overridden by AppOptions if env vars were set (but AppOptions are already applied).
// Actually, this function is called in New() before AppOptions are fully processed for watchdog.
// Let's check the call order: New() -> loadRuntimeSettingsFromFile() -> initializeWatchdog()
// But AppOptions are applied in NewApplicationConfig() which is called first.
// So at this point, options already has values from env vars. We should compare against
// defaults to see if env vars were set. But we don't have defaults stored.
// Simplest: Just apply file settings. If env vars were set, they're already in options.
// The file watcher handler will handle runtime changes properly by comparing with startupAppConfig.
func loadRuntimeSettingsFromFile(options *config.ApplicationConfig) {
settingsFile := filepath.Join(options.DynamicConfigsDir, "runtime_settings.json")
fileContent, err := os.ReadFile(settingsFile)
if err != nil {
if os.IsNotExist(err) {
log.Debug().Msg("runtime_settings.json not found, using defaults")
return
}
log.Warn().Err(err).Msg("failed to read runtime_settings.json")
return
}
var settings struct {
WatchdogEnabled *bool `json:"watchdog_enabled,omitempty"`
WatchdogIdleEnabled *bool `json:"watchdog_idle_enabled,omitempty"`
WatchdogBusyEnabled *bool `json:"watchdog_busy_enabled,omitempty"`
WatchdogIdleTimeout *string `json:"watchdog_idle_timeout,omitempty"`
WatchdogBusyTimeout *string `json:"watchdog_busy_timeout,omitempty"`
SingleBackend *bool `json:"single_backend,omitempty"`
ParallelBackendRequests *bool `json:"parallel_backend_requests,omitempty"`
}
if err := json.Unmarshal(fileContent, &settings); err != nil {
log.Warn().Err(err).Msg("failed to parse runtime_settings.json")
return
}
// At this point, options already has values from env vars (via AppOptions in run.go).
// To avoid env var duplication, we determine if env vars were set by checking if
// current values differ from defaults. Defaults are: false for bools, 0 for durations.
// If current value is at default, it likely wasn't set from env var, so we can apply file.
// If current value is non-default, it was likely set from env var, so we preserve it.
// Note: This means env vars explicitly setting to false/0 won't be distinguishable from defaults,
// but that's an acceptable limitation to avoid env var duplication.
if settings.WatchdogIdleEnabled != nil {
// Only apply if current value is default (false), suggesting it wasn't set from env var
if !options.WatchDogIdle {
options.WatchDogIdle = *settings.WatchdogIdleEnabled
if options.WatchDogIdle {
options.WatchDog = true
}
}
}
if settings.WatchdogBusyEnabled != nil {
if !options.WatchDogBusy {
options.WatchDogBusy = *settings.WatchdogBusyEnabled
if options.WatchDogBusy {
options.WatchDog = true
}
}
}
if settings.WatchdogIdleTimeout != nil {
// Only apply if current value is default (0), suggesting it wasn't set from env var
if options.WatchDogIdleTimeout == 0 {
dur, err := time.ParseDuration(*settings.WatchdogIdleTimeout)
if err == nil {
options.WatchDogIdleTimeout = dur
} else {
log.Warn().Err(err).Str("timeout", *settings.WatchdogIdleTimeout).Msg("invalid watchdog idle timeout in runtime_settings.json")
}
}
}
if settings.WatchdogBusyTimeout != nil {
if options.WatchDogBusyTimeout == 0 {
dur, err := time.ParseDuration(*settings.WatchdogBusyTimeout)
if err == nil {
options.WatchDogBusyTimeout = dur
} else {
log.Warn().Err(err).Str("timeout", *settings.WatchdogBusyTimeout).Msg("invalid watchdog busy timeout in runtime_settings.json")
}
}
}
if settings.SingleBackend != nil {
if !options.SingleBackend {
options.SingleBackend = *settings.SingleBackend
}
}
if settings.ParallelBackendRequests != nil {
if !options.ParallelBackendRequests {
options.ParallelBackendRequests = *settings.ParallelBackendRequests
}
}
if !options.WatchDogIdle && !options.WatchDogBusy {
if settings.WatchdogEnabled != nil && *settings.WatchdogEnabled {
options.WatchDog = true
}
}
log.Debug().Msg("Runtime settings loaded from runtime_settings.json")
}
// initializeWatchdog initializes the watchdog with current ApplicationConfig settings
func initializeWatchdog(application *Application, options *config.ApplicationConfig) {
if options.WatchDog {
wd := model.NewWatchDog(
application.ModelLoader(),
options.WatchDogBusyTimeout,
options.WatchDogIdleTimeout,
options.WatchDogBusy,
options.WatchDogIdle)
application.ModelLoader().SetWatchDog(wd)
go wd.Run()
go func() {
<-options.Context.Done()
log.Debug().Msgf("Context canceled, shutting down")
wd.Shutdown()
}()
}
}

View File

@@ -1,88 +0,0 @@
package application
import (
"time"
"github.com/mudler/LocalAI/pkg/model"
"github.com/rs/zerolog/log"
)
func (a *Application) StopWatchdog() error {
if a.watchdogStop != nil {
close(a.watchdogStop)
a.watchdogStop = nil
}
return nil
}
// startWatchdog starts the watchdog with current ApplicationConfig settings
// This is an internal method that assumes the caller holds the watchdogMutex
func (a *Application) startWatchdog() error {
appConfig := a.ApplicationConfig()
// Create new watchdog if enabled
if appConfig.WatchDog {
wd := model.NewWatchDog(
a.modelLoader,
appConfig.WatchDogBusyTimeout,
appConfig.WatchDogIdleTimeout,
appConfig.WatchDogBusy,
appConfig.WatchDogIdle)
a.modelLoader.SetWatchDog(wd)
// Create new stop channel
a.watchdogStop = make(chan bool, 1)
// Start watchdog goroutine
go wd.Run()
// Setup shutdown handler
go func() {
select {
case <-a.watchdogStop:
log.Debug().Msg("Watchdog stop signal received")
wd.Shutdown()
case <-appConfig.Context.Done():
log.Debug().Msg("Context canceled, shutting down watchdog")
wd.Shutdown()
}
}()
log.Info().Msg("Watchdog started with new settings")
} else {
log.Info().Msg("Watchdog disabled")
}
return nil
}
// StartWatchdog starts the watchdog with current ApplicationConfig settings
func (a *Application) StartWatchdog() error {
a.watchdogMutex.Lock()
defer a.watchdogMutex.Unlock()
return a.startWatchdog()
}
// RestartWatchdog restarts the watchdog with current ApplicationConfig settings
func (a *Application) RestartWatchdog() error {
a.watchdogMutex.Lock()
defer a.watchdogMutex.Unlock()
// Shutdown existing watchdog if running
if a.watchdogStop != nil {
close(a.watchdogStop)
a.watchdogStop = nil
}
// Shutdown existing watchdog if running
currentWD := a.modelLoader.GetWatchDog()
if currentWD != nil {
currentWD.Shutdown()
// Wait a bit for shutdown to complete
time.Sleep(100 * time.Millisecond)
}
// Start watchdog with new settings
return a.startWatchdog()
}

View File

@@ -40,7 +40,3 @@ func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negat
return fn, nil
}
// ImageGenerationFunc is a test-friendly indirection to call image generation logic.
// Tests can override this variable to provide a stub implementation.
var ImageGenerationFunc = ImageGeneration

View File

@@ -3,6 +3,7 @@ package backend
import (
"context"
"encoding/json"
"fmt"
"regexp"
"slices"
"strings"
@@ -25,7 +26,6 @@ type LLMResponse struct {
Response string // should this be []byte?
Usage TokenUsage
AudioOutput string
Logprobs *schema.Logprobs // Logprobs from the backend response
}
type TokenUsage struct {
@@ -35,7 +35,7 @@ type TokenUsage struct {
TimingTokenGeneration float64
}
func ModelInference(ctx context.Context, s string, messages schema.Messages, images, videos, audios []string, loader *model.ModelLoader, c *config.ModelConfig, cl *config.ModelConfigLoader, o *config.ApplicationConfig, tokenCallback func(string, TokenUsage) bool, tools string, toolChoice string, logprobs *int, topLogprobs *int, logitBias map[string]float64) (func() (LLMResponse, error), error) {
func ModelInference(ctx context.Context, s string, messages []schema.Message, images, videos, audios []string, loader *model.ModelLoader, c *config.ModelConfig, cl *config.ModelConfigLoader, o *config.ApplicationConfig, tokenCallback func(string, TokenUsage) bool) (func() (LLMResponse, error), error) {
modelFile := c.Model
// Check if the modelFile exists, if it doesn't try to load it from the gallery
@@ -47,7 +47,7 @@ func ModelInference(ctx context.Context, s string, messages schema.Messages, ima
if !slices.Contains(modelNames, c.Name) {
utils.ResetDownloadTimers()
// if we failed to load the model, we try to download it
err := gallery.InstallModelFromGallery(ctx, o.Galleries, o.BackendGalleries, o.SystemState, loader, c.Name, gallery.GalleryModel{}, utils.DisplayDownloadFunction, o.EnforcePredownloadScans, o.AutoloadBackendGalleries)
err := gallery.InstallModelFromGallery(o.Galleries, o.BackendGalleries, o.SystemState, loader, c.Name, gallery.GalleryModel{}, utils.DisplayDownloadFunction, o.EnforcePredownloadScans, o.AutoloadBackendGalleries)
if err != nil {
log.Error().Err(err).Msgf("failed to install model %q from gallery", modelFile)
//return nil, err
@@ -65,8 +65,29 @@ func ModelInference(ctx context.Context, s string, messages schema.Messages, ima
var protoMessages []*proto.Message
// if we are using the tokenizer template, we need to convert the messages to proto messages
// unless the prompt has already been tokenized (non-chat endpoints + functions)
if c.TemplateConfig.UseTokenizerTemplate && len(messages) > 0 {
protoMessages = messages.ToProto()
if c.TemplateConfig.UseTokenizerTemplate && s == "" {
protoMessages = make([]*proto.Message, len(messages), len(messages))
for i, message := range messages {
protoMessages[i] = &proto.Message{
Role: message.Role,
}
switch ct := message.Content.(type) {
case string:
protoMessages[i].Content = ct
case []interface{}:
// If using the tokenizer template, in case of multimodal we want to keep the multimodal content as and return only strings here
data, _ := json.Marshal(ct)
resultData := []struct {
Text string `json:"text"`
}{}
json.Unmarshal(data, &resultData)
for _, r := range resultData {
protoMessages[i].Content += r.Text
}
default:
return nil, fmt.Errorf("unsupported type for schema.Message.Content for inference: %T", ct)
}
}
}
// in GRPC, the backend is supposed to answer to 1 single token if stream is not supported
@@ -78,21 +99,6 @@ func ModelInference(ctx context.Context, s string, messages schema.Messages, ima
opts.Images = images
opts.Videos = videos
opts.Audios = audios
opts.Tools = tools
opts.ToolChoice = toolChoice
if logprobs != nil {
opts.Logprobs = int32(*logprobs)
}
if topLogprobs != nil {
opts.TopLogprobs = int32(*topLogprobs)
}
if len(logitBias) > 0 {
// Serialize logit_bias map to JSON string for proto
logitBiasJSON, err := json.Marshal(logitBias)
if err == nil {
opts.LogitBias = string(logitBiasJSON)
}
}
tokenUsage := TokenUsage{}
@@ -124,7 +130,6 @@ func ModelInference(ctx context.Context, s string, messages schema.Messages, ima
}
ss := ""
var logprobs *schema.Logprobs
var partialRune []byte
err := inferenceModel.PredictStream(ctx, opts, func(reply *proto.Reply) {
@@ -136,14 +141,6 @@ func ModelInference(ctx context.Context, s string, messages schema.Messages, ima
tokenUsage.TimingTokenGeneration = reply.TimingTokenGeneration
tokenUsage.TimingPromptProcessing = reply.TimingPromptProcessing
// Parse logprobs from reply if present (collect from last chunk that has them)
if len(reply.Logprobs) > 0 {
var parsedLogprobs schema.Logprobs
if err := json.Unmarshal(reply.Logprobs, &parsedLogprobs); err == nil {
logprobs = &parsedLogprobs
}
}
// Process complete runes and accumulate them
var completeRunes []byte
for len(partialRune) > 0 {
@@ -169,7 +166,6 @@ func ModelInference(ctx context.Context, s string, messages schema.Messages, ima
return LLMResponse{
Response: ss,
Usage: tokenUsage,
Logprobs: logprobs,
}, err
} else {
// TODO: Is the chicken bit the only way to get here? is that acceptable?
@@ -192,19 +188,9 @@ func ModelInference(ctx context.Context, s string, messages schema.Messages, ima
response = c.TemplateConfig.ReplyPrefix + response
}
// Parse logprobs from reply if present
var logprobs *schema.Logprobs
if len(reply.Logprobs) > 0 {
var parsedLogprobs schema.Logprobs
if err := json.Unmarshal(reply.Logprobs, &parsedLogprobs); err == nil {
logprobs = &parsedLogprobs
}
}
return LLMResponse{
Response: response,
Usage: tokenUsage,
Logprobs: logprobs,
}, err
}
}

View File

@@ -129,6 +129,7 @@ func grpcModelOpts(c config.ModelConfig) *pb.ModelOptions {
triggers = append(triggers, &pb.GrammarTrigger{
Word: t.Word,
})
}
return &pb.ModelOptions{
@@ -212,7 +213,7 @@ func gRPCPredictOpts(c config.ModelConfig, modelPath string) *pb.PredictOptions
}
}
pbOpts := &pb.PredictOptions{
return &pb.PredictOptions{
Temperature: float32(*c.Temperature),
TopP: float32(*c.TopP),
NDraft: c.NDraft,
@@ -249,6 +250,4 @@ func gRPCPredictOpts(c config.ModelConfig, modelPath string) *pb.PredictOptions
TailFreeSamplingZ: float32(*c.TFZ),
TypicalP: float32(*c.TypicalP),
}
// Logprobs and TopLogprobs are set by the caller if provided
return pbOpts
}

View File

@@ -60,7 +60,7 @@ func SoundGeneration(
// return RPC error if any
if !res.Success {
return "", nil, fmt.Errorf("error during sound generation: %s", res.Message)
return "", nil, fmt.Errorf(res.Message)
}
return filePath, res, err

View File

@@ -70,7 +70,7 @@ func ModelTTS(
// return RPC error if any
if !res.Success {
return "", nil, fmt.Errorf("error during TTS: %s", res.Message)
return "", nil, fmt.Errorf(res.Message)
}
return filePath, res, err

87
core/cli/api/p2p.go Normal file
View File

@@ -0,0 +1,87 @@
package cli_api
import (
"context"
"fmt"
"net"
"os"
"strings"
"github.com/mudler/LocalAI/core/application"
"github.com/mudler/LocalAI/core/p2p"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/edgevpn/pkg/node"
"github.com/rs/zerolog/log"
)
func StartP2PStack(ctx context.Context, address, token, networkID string, federated bool, app *application.Application) error {
var n *node.Node
// Here we are avoiding creating multiple nodes:
// - if the federated mode is enabled, we create a federated node and expose a service
// - exposing a service creates a node with specific options, and we don't want to create another node
// If the federated mode is enabled, we expose a service to the local instance running
// at r.Address
if federated {
_, port, err := net.SplitHostPort(address)
if err != nil {
return err
}
// Here a new node is created and started
// and a service is exposed by the node
node, err := p2p.ExposeService(ctx, "localhost", port, token, p2p.NetworkID(networkID, p2p.FederatedID))
if err != nil {
return err
}
if err := p2p.ServiceDiscoverer(ctx, node, token, p2p.NetworkID(networkID, p2p.FederatedID), nil, false); err != nil {
return err
}
n = node
// start node sync in the background
if err := p2p.Sync(ctx, node, app); err != nil {
return err
}
}
// If the p2p mode is enabled, we start the service discovery
if token != "" {
// If a node wasn't created previously, create it
if n == nil {
node, err := p2p.NewNode(token)
if err != nil {
return err
}
err = node.Start(ctx)
if err != nil {
return fmt.Errorf("starting new node: %w", err)
}
n = node
}
// Attach a ServiceDiscoverer to the p2p node
log.Info().Msg("Starting P2P server discovery...")
if err := p2p.ServiceDiscoverer(ctx, n, token, p2p.NetworkID(networkID, p2p.WorkerID), func(serviceID string, node schema.NodeData) {
var tunnelAddresses []string
for _, v := range p2p.GetAvailableNodes(p2p.NetworkID(networkID, p2p.WorkerID)) {
if v.IsOnline() {
tunnelAddresses = append(tunnelAddresses, v.TunnelAddress)
} else {
log.Info().Msgf("Node %s is offline", v.ID)
}
}
tunnelEnvVar := strings.Join(tunnelAddresses, ",")
os.Setenv("LLAMACPP_GRPC_SERVERS", tunnelEnvVar)
log.Debug().Msgf("setting LLAMACPP_GRPC_SERVERS to %s", tunnelEnvVar)
}, true); err != nil {
return err
}
}
return nil
}

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