WIP

.air.toml

@@ -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

.env

@@ -32,6 +32,15 @@
 # Forces shutdown of the backends if busy (only if LOCALAI_SINGLE_ACTIVE_BACKEND is set)
 # LOCALAI_FORCE_BACKEND_SHUTDOWN=true
 
+## Specify a build type. Available: cublas, openblas, clblas.
+## cuBLAS: This is a GPU-accelerated version of the complete standard BLAS (Basic Linear Algebra Subprograms) library. It's provided by Nvidia and is part of their CUDA toolkit.
+## OpenBLAS: This is an open-source implementation of the BLAS library that aims to provide highly optimized code for various platforms. It includes support for multi-threading and can be compiled to use hardware-specific features for additional performance. OpenBLAS can run on many kinds of hardware, including CPUs from Intel, AMD, and ARM.
+## clBLAS:   This is an open-source implementation of the BLAS library that uses OpenCL, a framework for writing programs that execute across heterogeneous platforms consisting of CPUs, GPUs, and other processors. clBLAS is designed to take advantage of the parallel computing power of GPUs but can also run on any hardware that supports OpenCL. This includes hardware from different vendors like Nvidia, AMD, and Intel.
+# BUILD_TYPE=openblas
+
+## Uncomment and set to true to enable rebuilding from source
+# REBUILD=true
+
 ## Path where to store generated images
 # LOCALAI_IMAGE_PATH=/tmp/generated/images
 

.github/gallery-agent/agent.go

@@ -1,445 +0,0 @@
-package main
-
-import (
-	"context"
-	"encoding/json"
-	"fmt"
-	"io"
-	"net/http"
-	"os"
-	"regexp"
-	"slices"
-	"strings"
-
-	"github.com/ghodss/yaml"
-	hfapi "github.com/mudler/LocalAI/pkg/huggingface-api"
-	cogito "github.com/mudler/cogito"
-
-	"github.com/mudler/cogito/structures"
-	"github.com/sashabaranov/go-openai/jsonschema"
-)
-
-var (
-	openAIModel      = os.Getenv("OPENAI_MODEL")
-	openAIKey        = os.Getenv("OPENAI_KEY")
-	openAIBaseURL    = os.Getenv("OPENAI_BASE_URL")
-	galleryIndexPath = os.Getenv("GALLERY_INDEX_PATH")
-	//defaultclient
-	llm = cogito.NewOpenAILLM(openAIModel, openAIKey, openAIBaseURL)
-)
-
-// cleanTextContent removes trailing spaces, tabs, and normalizes line endings
-// to prevent YAML linting issues like trailing spaces and multiple empty lines
-func cleanTextContent(text string) string {
-	lines := strings.Split(text, "\n")
-	var cleanedLines []string
-	var prevEmpty bool
-	for _, line := range lines {
-		// Remove all trailing whitespace (spaces, tabs, etc.)
-		trimmed := strings.TrimRight(line, " \t\r")
-		// Avoid multiple consecutive empty lines
-		if trimmed == "" {
-			if !prevEmpty {
-				cleanedLines = append(cleanedLines, "")
-			}
-			prevEmpty = true
-		} else {
-			cleanedLines = append(cleanedLines, trimmed)
-			prevEmpty = false
-		}
-	}
-	// Remove trailing empty lines from the result
-	result := strings.Join(cleanedLines, "\n")
-	return stripThinkingTags(strings.TrimRight(result, "\n"))
-}
-
-type galleryModel struct {
-	Name string   `yaml:"name"`
-	Urls []string `yaml:"urls"`
-}
-
-// isModelExisting checks if a specific model ID exists in the gallery using text search
-func isModelExisting(modelID string) (bool, error) {
-	indexPath := getGalleryIndexPath()
-	content, err := os.ReadFile(indexPath)
-	if err != nil {
-		return false, fmt.Errorf("failed to read %s: %w", indexPath, err)
-	}
-
-	var galleryModels []galleryModel
-
-	err = yaml.Unmarshal(content, &galleryModels)
-	if err != nil {
-		return false, fmt.Errorf("failed to unmarshal %s: %w", indexPath, err)
-	}
-
-	for _, galleryModel := range galleryModels {
-		if slices.Contains(galleryModel.Urls, modelID) {
-			return true, nil
-		}
-	}
-
-	return false, nil
-}
-
-// filterExistingModels removes models that already exist in the gallery
-func filterExistingModels(models []ProcessedModel) ([]ProcessedModel, error) {
-	var filteredModels []ProcessedModel
-	for _, model := range models {
-		exists, err := isModelExisting(model.ModelID)
-		if err != nil {
-			fmt.Printf("Error checking if model %s exists: %v, skipping\n", model.ModelID, err)
-			continue
-		}
-
-		if !exists {
-			filteredModels = append(filteredModels, model)
-		} else {
-			fmt.Printf("Skipping existing model: %s\n", model.ModelID)
-		}
-	}
-
-	fmt.Printf("Filtered out %d existing models, %d new models remaining\n",
-		len(models)-len(filteredModels), len(filteredModels))
-
-	return filteredModels, nil
-}
-
-// getGalleryIndexPath returns the gallery index file path, with a default fallback
-func getGalleryIndexPath() string {
-	if galleryIndexPath != "" {
-		return galleryIndexPath
-	}
-	return "gallery/index.yaml"
-}
-
-func stripThinkingTags(content string) string {
-	// Remove content between <thinking> and </thinking> (including multi-line)
-	content = regexp.MustCompile(`(?s)<thinking>.*?</thinking>`).ReplaceAllString(content, "")
-	// Remove content between <think> and </think> (including multi-line)
-	content = regexp.MustCompile(`(?s)<think>.*?</think>`).ReplaceAllString(content, "")
-	// Clean up any extra whitespace
-	content = strings.TrimSpace(content)
-	return content
-}
-
-func getRealReadme(ctx context.Context, repository string) (string, error) {
-	// Create a conversation fragment
-	fragment := cogito.NewEmptyFragment().
-		AddMessage("user",
-			`Your task is to get a clear description of a large language model from huggingface by using the provided tool. I will share with you a repository that might be quantized, and as such probably not by the original model author. We need to get the real  description of the model, and not the one that might be quantized. You will have to call the tool to get the readme more than once by figuring out from the quantized readme which is the base model readme. This is the repository: `+repository)
-
-	// Execute with tools
-	result, err := cogito.ExecuteTools(llm, fragment,
-		cogito.WithIterations(3),
-		cogito.WithMaxAttempts(3),
-		cogito.WithTools(&HFReadmeTool{client: hfapi.NewClient()}))
-	if err != nil {
-		return "", err
-	}
-
-	result = result.AddMessage("user", "Describe the model in a clear and concise way that can be shared in a model gallery.")
-
-	// Get a response
-	newFragment, err := llm.Ask(ctx, result)
-	if err != nil {
-		return "", err
-	}
-
-	content := newFragment.LastMessage().Content
-	return cleanTextContent(content), nil
-}
-
-func selectMostInterestingModels(ctx context.Context, searchResult *SearchResult) ([]ProcessedModel, error) {
-
-	if len(searchResult.Models) == 1 {
-		return searchResult.Models, nil
-	}
-
-	// Create a conversation fragment
-	fragment := cogito.NewEmptyFragment().
-		AddMessage("user",
-			`Your task is to analyze a list of AI models and select the most interesting ones for a model gallery. You will be given detailed information about multiple models including their metadata, file information, and README content.
-
-Consider the following criteria when selecting models:
-1. Model popularity (download count)
-2. Model recency (last modified date)
-3. Model completeness (has preferred model file, README, etc.)
-4. Model uniqueness (not duplicates or very similar models)
-5. Model quality (based on README content and description)
-6. Model utility (practical applications)
-
-You should select models that would be most valuable for users browsing a model gallery. Prioritize models that are:
-- Well-documented with clear READMEs
-- Recently updated
-- Popular (high download count)
-- Have the preferred quantization format available
-- Offer unique capabilities or are from reputable authors
-
-Return your analysis and selection reasoning.`)
-
-	// Add the search results as context
-	modelsInfo := fmt.Sprintf("Found %d models matching '%s' with quantization preference '%s':\n\n",
-		searchResult.TotalModelsFound, searchResult.SearchTerm, searchResult.Quantization)
-
-	for i, model := range searchResult.Models {
-		modelsInfo += fmt.Sprintf("Model %d:\n", i+1)
-		modelsInfo += fmt.Sprintf("  ID: %s\n", model.ModelID)
-		modelsInfo += fmt.Sprintf("  Author: %s\n", model.Author)
-		modelsInfo += fmt.Sprintf("  Downloads: %d\n", model.Downloads)
-		modelsInfo += fmt.Sprintf("  Last Modified: %s\n", model.LastModified)
-		modelsInfo += fmt.Sprintf("  Files: %d files\n", len(model.Files))
-
-		if model.PreferredModelFile != nil {
-			modelsInfo += fmt.Sprintf("  Preferred Model File: %s (%d bytes)\n",
-				model.PreferredModelFile.Path, model.PreferredModelFile.Size)
-		} else {
-			modelsInfo += "  No preferred model file found\n"
-		}
-
-		if model.ReadmeContent != "" {
-			modelsInfo += fmt.Sprintf("  README: %s\n", model.ReadmeContent)
-		}
-
-		if model.ProcessingError != "" {
-			modelsInfo += fmt.Sprintf("  Processing Error: %s\n", model.ProcessingError)
-		}
-
-		modelsInfo += "\n"
-	}
-
-	fragment = fragment.AddMessage("user", modelsInfo)
-
-	fragment = fragment.AddMessage("user", "Based on your analysis, select the top 5 most interesting models and provide a brief explanation for each selection. Also, create a filtered SearchResult with only the selected models. Return just a list of repositories IDs, you will later be asked to output it as a JSON array with the json tool.")
-
-	// Get a response
-	newFragment, err := llm.Ask(ctx, fragment)
-	if err != nil {
-		return nil, err
-	}
-
-	fmt.Println(newFragment.LastMessage().Content)
-	repositories := struct {
-		Repositories []string `json:"repositories"`
-	}{}
-
-	s := structures.Structure{
-		Schema: jsonschema.Definition{
-			Type:                 jsonschema.Object,
-			AdditionalProperties: false,
-			Properties: map[string]jsonschema.Definition{
-				"repositories": {
-					Type:        jsonschema.Array,
-					Items:       &jsonschema.Definition{Type: jsonschema.String},
-					Description: "The trending repositories IDs",
-				},
-			},
-			Required: []string{"repositories"},
-		},
-		Object: &repositories,
-	}
-
-	err = newFragment.ExtractStructure(ctx, llm, s)
-	if err != nil {
-		return nil, err
-	}
-
-	filteredModels := []ProcessedModel{}
-	for _, m := range searchResult.Models {
-		if slices.Contains(repositories.Repositories, m.ModelID) {
-			filteredModels = append(filteredModels, m)
-		}
-	}
-
-	return filteredModels, nil
-}
-
-// ModelMetadata represents extracted metadata from a model
-type ModelMetadata struct {
-	Tags    []string `json:"tags"`
-	License string   `json:"license"`
-}
-
-// extractModelMetadata extracts tags and license from model README and documentation
-func extractModelMetadata(ctx context.Context, model ProcessedModel) ([]string, string, error) {
-	// Create a conversation fragment
-	fragment := cogito.NewEmptyFragment().
-		AddMessage("user",
-			`Your task is to extract metadata from an AI model's README and documentation. You will be provided with:
-1. Model information (ID, author, description)
-2. README content
-
-You need to extract:
-1. **Tags**: An array of relevant tags that describe the model. Use common tags from the gallery such as:
-   - llm, gguf, gpu, cpu, multimodal, image-to-text, text-to-text, text-to-speech, tts
-   - thinking, reasoning, chat, instruction-tuned, code, vision
-   - Model family names (e.g., llama, qwen, mistral, gemma) if applicable
-   - Any other relevant descriptive tags
-   Select 3-8 most relevant tags.
-
-2. **License**: The license identifier (e.g., "apache-2.0", "mit", "llama2", "gpl-3.0", "bsd", "cc-by-4.0").
-   If no license is found, return an empty string.
-
-Return the extracted metadata in a structured format.`)
-
-	// Add model information
-	modelInfo := "Model Information:\n"
-	modelInfo += fmt.Sprintf("  ID: %s\n", model.ModelID)
-	modelInfo += fmt.Sprintf("  Author: %s\n", model.Author)
-	modelInfo += fmt.Sprintf("  Downloads: %d\n", model.Downloads)
-	if model.ReadmeContent != "" {
-		modelInfo += fmt.Sprintf("  README Content:\n%s\n", model.ReadmeContent)
-	} else if model.ReadmeContentPreview != "" {
-		modelInfo += fmt.Sprintf("  README Preview: %s\n", model.ReadmeContentPreview)
-	}
-
-	fragment = fragment.AddMessage("user", modelInfo)
-	fragment = fragment.AddMessage("user", "Extract the tags and license from the model information. Return the metadata as a JSON object with 'tags' (array of strings) and 'license' (string).")
-
-	// Get a response
-	newFragment, err := llm.Ask(ctx, fragment)
-	if err != nil {
-		return nil, "", err
-	}
-
-	// Extract structured metadata
-	metadata := ModelMetadata{}
-
-	s := structures.Structure{
-		Schema: jsonschema.Definition{
-			Type:                 jsonschema.Object,
-			AdditionalProperties: false,
-			Properties: map[string]jsonschema.Definition{
-				"tags": {
-					Type:        jsonschema.Array,
-					Items:       &jsonschema.Definition{Type: jsonschema.String},
-					Description: "Array of relevant tags describing the model",
-				},
-				"license": {
-					Type:        jsonschema.String,
-					Description: "License identifier (e.g., apache-2.0, mit, llama2). Empty string if not found.",
-				},
-			},
-			Required: []string{"tags", "license"},
-		},
-		Object: &metadata,
-	}
-
-	err = newFragment.ExtractStructure(ctx, llm, s)
-	if err != nil {
-		return nil, "", err
-	}
-
-	return metadata.Tags, metadata.License, nil
-}
-
-// extractIconFromReadme scans the README content for image URLs and returns the first suitable icon URL found
-func extractIconFromReadme(readmeContent string) string {
-	if readmeContent == "" {
-		return ""
-	}
-
-	// Regular expressions to match image URLs in various formats (case-insensitive)
-	// Match markdown image syntax: ![alt](url) - case insensitive extensions
-	markdownImageRegex := regexp.MustCompile(`(?i)!\[[^\]]*\]\(([^)]+\.(png|jpg|jpeg|svg|webp|gif))\)`)
-	// Match HTML img tags: <img src="url">
-	htmlImageRegex := regexp.MustCompile(`(?i)<img[^>]+src=["']([^"']+\.(png|jpg|jpeg|svg|webp|gif))["']`)
-	// Match plain URLs ending with image extensions
-	plainImageRegex := regexp.MustCompile(`(?i)https?://[^\s<>"']+\.(png|jpg|jpeg|svg|webp|gif)`)
-
-	// Try markdown format first
-	matches := markdownImageRegex.FindStringSubmatch(readmeContent)
-	if len(matches) > 1 && matches[1] != "" {
-		url := strings.TrimSpace(matches[1])
-		// Prefer HuggingFace CDN URLs or absolute URLs
-		if strings.HasPrefix(strings.ToLower(url), "http") {
-			return url
-		}
-	}
-
-	// Try HTML img tags
-	matches = htmlImageRegex.FindStringSubmatch(readmeContent)
-	if len(matches) > 1 && matches[1] != "" {
-		url := strings.TrimSpace(matches[1])
-		if strings.HasPrefix(strings.ToLower(url), "http") {
-			return url
-		}
-	}
-
-	// Try plain URLs
-	matches = plainImageRegex.FindStringSubmatch(readmeContent)
-	if len(matches) > 0 {
-		url := strings.TrimSpace(matches[0])
-		if strings.HasPrefix(strings.ToLower(url), "http") {
-			return url
-		}
-	}
-
-	return ""
-}
-
-// getHuggingFaceAvatarURL attempts to get the HuggingFace avatar URL for a user
-func getHuggingFaceAvatarURL(author string) string {
-	if author == "" {
-		return ""
-	}
-
-	// Try to fetch user info from HuggingFace API
-	// HuggingFace API endpoint: https://huggingface.co/api/users/{username}
-	baseURL := "https://huggingface.co"
-	userURL := fmt.Sprintf("%s/api/users/%s", baseURL, author)
-
-	req, err := http.NewRequest("GET", userURL, nil)
-	if err != nil {
-		return ""
-	}
-
-	client := &http.Client{}
-	resp, err := client.Do(req)
-	if err != nil {
-		return ""
-	}
-	defer resp.Body.Close()
-
-	if resp.StatusCode != http.StatusOK {
-		return ""
-	}
-
-	// Parse the response to get avatar URL
-	var userInfo map[string]interface{}
-	body, err := io.ReadAll(resp.Body)
-	if err != nil {
-		return ""
-	}
-
-	if err := json.Unmarshal(body, &userInfo); err != nil {
-		return ""
-	}
-
-	// Try to extract avatar URL from response
-	if avatar, ok := userInfo["avatarUrl"].(string); ok && avatar != "" {
-		return avatar
-	}
-	if avatar, ok := userInfo["avatar"].(string); ok && avatar != "" {
-		return avatar
-	}
-
-	return ""
-}
-
-// extractModelIcon extracts icon URL from README or falls back to HuggingFace avatar
-func extractModelIcon(model ProcessedModel) string {
-	// First, try to extract icon from README
-	if icon := extractIconFromReadme(model.ReadmeContent); icon != "" {
-		return icon
-	}
-
-	// Fallback: Try to get HuggingFace user avatar
-	if model.Author != "" {
-		if avatar := getHuggingFaceAvatarURL(model.Author); avatar != "" {
-			return avatar
-		}
-	}
-
-	return ""
-}

.github/gallery-agent/gallery.go

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

.github/gallery-agent/main.go

@@ -1,383 +0,0 @@
-package main
-
-import (
-	"context"
-	"encoding/json"
-	"fmt"
-	"os"
-	"strconv"
-	"strings"
-	"time"
-
-	hfapi "github.com/mudler/LocalAI/pkg/huggingface-api"
-)
-
-// ProcessedModelFile represents a processed model file with additional metadata
-type ProcessedModelFile struct {
-	Path     string `json:"path"`
-	Size     int64  `json:"size"`
-	SHA256   string `json:"sha256"`
-	IsReadme bool   `json:"is_readme"`
-	FileType string `json:"file_type"` // "model", "readme", "other"
-}
-
-// ProcessedModel represents a processed model with all gathered metadata
-type ProcessedModel struct {
-	ModelID                 string               `json:"model_id"`
-	Author                  string               `json:"author"`
-	Downloads               int                  `json:"downloads"`
-	LastModified            string               `json:"last_modified"`
-	Files                   []ProcessedModelFile `json:"files"`
-	PreferredModelFile      *ProcessedModelFile  `json:"preferred_model_file,omitempty"`
-	ReadmeFile              *ProcessedModelFile  `json:"readme_file,omitempty"`
-	ReadmeContent           string               `json:"readme_content,omitempty"`
-	ReadmeContentPreview    string               `json:"readme_content_preview,omitempty"`
-	QuantizationPreferences []string             `json:"quantization_preferences"`
-	ProcessingError         string               `json:"processing_error,omitempty"`
-	Tags                    []string             `json:"tags,omitempty"`
-	License                 string               `json:"license,omitempty"`
-	Icon                    string               `json:"icon,omitempty"`
-}
-
-// SearchResult represents the complete result of searching and processing models
-type SearchResult struct {
-	SearchTerm       string           `json:"search_term"`
-	Limit            int              `json:"limit"`
-	Quantization     string           `json:"quantization"`
-	TotalModelsFound int              `json:"total_models_found"`
-	Models           []ProcessedModel `json:"models"`
-	FormattedOutput  string           `json:"formatted_output"`
-}
-
-// AddedModelSummary represents a summary of models added to the gallery
-type AddedModelSummary struct {
-	SearchTerm     string   `json:"search_term"`
-	TotalFound     int      `json:"total_found"`
-	ModelsAdded    int      `json:"models_added"`
-	AddedModelIDs  []string `json:"added_model_ids"`
-	AddedModelURLs []string `json:"added_model_urls"`
-	Quantization   string   `json:"quantization"`
-	ProcessingTime string   `json:"processing_time"`
-}
-
-func main() {
-	startTime := time.Now()
-
-	// Check for synthetic mode
-	syntheticMode := os.Getenv("SYNTHETIC_MODE")
-	if syntheticMode == "true" || syntheticMode == "1" {
-		fmt.Println("Running in SYNTHETIC MODE - generating random test data")
-		err := runSyntheticMode()
-		if err != nil {
-			fmt.Fprintf(os.Stderr, "Error in synthetic mode: %v\n", err)
-			os.Exit(1)
-		}
-		return
-	}
-
-	// Get configuration from environment variables
-	searchTerm := os.Getenv("SEARCH_TERM")
-	if searchTerm == "" {
-		searchTerm = "GGUF"
-	}
-
-	limitStr := os.Getenv("LIMIT")
-	if limitStr == "" {
-		limitStr = "5"
-	}
-	limit, err := strconv.Atoi(limitStr)
-	if err != nil {
-		fmt.Fprintf(os.Stderr, "Error parsing LIMIT: %v\n", err)
-		os.Exit(1)
-	}
-
-	quantization := os.Getenv("QUANTIZATION")
-
-	maxModels := os.Getenv("MAX_MODELS")
-	if maxModels == "" {
-		maxModels = "1"
-	}
-	maxModelsInt, err := strconv.Atoi(maxModels)
-	if err != nil {
-		fmt.Fprintf(os.Stderr, "Error parsing MAX_MODELS: %v\n", err)
-		os.Exit(1)
-	}
-
-	// Print configuration
-	fmt.Printf("Gallery Agent Configuration:\n")
-	fmt.Printf("  Search Term: %s\n", searchTerm)
-	fmt.Printf("  Limit: %d\n", limit)
-	fmt.Printf("  Quantization: %s\n", quantization)
-	fmt.Printf("  Max Models to Add: %d\n", maxModelsInt)
-	fmt.Printf("  Gallery Index Path: %s\n", os.Getenv("GALLERY_INDEX_PATH"))
-	fmt.Println()
-
-	result, err := searchAndProcessModels(searchTerm, limit, quantization)
-	if err != nil {
-		fmt.Fprintf(os.Stderr, "Error: %v\n", err)
-		os.Exit(1)
-	}
-
-	fmt.Println(result.FormattedOutput)
-	var models []ProcessedModel
-
-	if len(result.Models) > 1 {
-		fmt.Println("More than one model found (", len(result.Models), "), using AI agent to select the most interesting models")
-		for _, model := range result.Models {
-			fmt.Println("Model: ", model.ModelID)
-		}
-		// Use AI agent to select the most interesting models
-		fmt.Println("Using AI agent to select the most interesting models...")
-		models, err = selectMostInterestingModels(context.Background(), result)
-		if err != nil {
-			fmt.Fprintf(os.Stderr, "Error in model selection: %v\n", err)
-			// Continue with original result if selection fails
-			models = result.Models
-		}
-	} else if len(result.Models) == 1 {
-		models = result.Models
-		fmt.Println("Only one model found, using it directly")
-	}
-
-	fmt.Print(models)
-
-	// Filter out models that already exist in the gallery
-	fmt.Println("Filtering out existing models...")
-	models, err = filterExistingModels(models)
-	if err != nil {
-		fmt.Fprintf(os.Stderr, "Error filtering existing models: %v\n", err)
-		os.Exit(1)
-	}
-
-	// Limit to maxModelsInt after filtering
-	if len(models) > maxModelsInt {
-		models = models[:maxModelsInt]
-	}
-
-	// Track added models for summary
-	var addedModelIDs []string
-	var addedModelURLs []string
-
-	// Generate YAML entries and append to gallery/index.yaml
-	if len(models) > 0 {
-		for _, model := range models {
-			addedModelIDs = append(addedModelIDs, model.ModelID)
-			// Generate Hugging Face URL for the model
-			modelURL := fmt.Sprintf("https://huggingface.co/%s", model.ModelID)
-			addedModelURLs = append(addedModelURLs, modelURL)
-		}
-		fmt.Println("Generating YAML entries for selected models...")
-		err = generateYAMLForModels(context.Background(), models, quantization)
-		if err != nil {
-			fmt.Fprintf(os.Stderr, "Error generating YAML entries: %v\n", err)
-			os.Exit(1)
-		}
-	} else {
-		fmt.Println("No new models to add to the gallery.")
-	}
-
-	// Create and write summary
-	processingTime := time.Since(startTime).String()
-	summary := AddedModelSummary{
-		SearchTerm:     searchTerm,
-		TotalFound:     result.TotalModelsFound,
-		ModelsAdded:    len(addedModelIDs),
-		AddedModelIDs:  addedModelIDs,
-		AddedModelURLs: addedModelURLs,
-		Quantization:   quantization,
-		ProcessingTime: processingTime,
-	}
-
-	// Write summary to file
-	summaryData, err := json.MarshalIndent(summary, "", "  ")
-	if err != nil {
-		fmt.Fprintf(os.Stderr, "Error marshaling summary: %v\n", err)
-	} else {
-		err = os.WriteFile("gallery-agent-summary.json", summaryData, 0644)
-		if err != nil {
-			fmt.Fprintf(os.Stderr, "Error writing summary file: %v\n", err)
-		} else {
-			fmt.Printf("Summary written to gallery-agent-summary.json\n")
-		}
-	}
-}
-
-func searchAndProcessModels(searchTerm string, limit int, quantization string) (*SearchResult, error) {
-	client := hfapi.NewClient()
-	var outputBuilder strings.Builder
-
-	fmt.Println("Searching for models...")
-	// Initialize the result struct
-	result := &SearchResult{
-		SearchTerm:   searchTerm,
-		Limit:        limit,
-		Quantization: quantization,
-		Models:       []ProcessedModel{},
-	}
-
-	models, err := client.GetLatest(searchTerm, limit)
-	if err != nil {
-		return nil, fmt.Errorf("failed to fetch models: %w", err)
-	}
-
-	fmt.Println("Models found:", len(models))
-	result.TotalModelsFound = len(models)
-
-	if len(models) == 0 {
-		outputBuilder.WriteString("No models found.\n")
-		result.FormattedOutput = outputBuilder.String()
-		return result, nil
-	}
-
-	outputBuilder.WriteString(fmt.Sprintf("Found %d models matching '%s':\n\n", len(models), searchTerm))
-
-	// Process each model
-	for i, model := range models {
-		outputBuilder.WriteString(fmt.Sprintf("%d. Processing Model: %s\n", i+1, model.ModelID))
-		outputBuilder.WriteString(fmt.Sprintf("   Author: %s\n", model.Author))
-		outputBuilder.WriteString(fmt.Sprintf("   Downloads: %d\n", model.Downloads))
-		outputBuilder.WriteString(fmt.Sprintf("   Last Modified: %s\n", model.LastModified))
-
-		// Initialize processed model struct
-		processedModel := ProcessedModel{
-			ModelID:                 model.ModelID,
-			Author:                  model.Author,
-			Downloads:               model.Downloads,
-			LastModified:            model.LastModified,
-			QuantizationPreferences: []string{quantization, "Q4_K_M", "Q4_K_S", "Q3_K_M", "Q2_K"},
-		}
-
-		// Get detailed model information
-		details, err := client.GetModelDetails(model.ModelID)
-		if err != nil {
-			errorMsg := fmt.Sprintf("   Error getting model details: %v\n", err)
-			outputBuilder.WriteString(errorMsg)
-			processedModel.ProcessingError = err.Error()
-			result.Models = append(result.Models, processedModel)
-			continue
-		}
-
-		// Define quantization preferences (in order of preference)
-		quantizationPreferences := []string{quantization, "Q4_K_M", "Q4_K_S", "Q3_K_M", "Q2_K"}
-
-		// Find preferred model file
-		preferredModelFile := hfapi.FindPreferredModelFile(details.Files, quantizationPreferences)
-
-		// Process files
-		processedFiles := make([]ProcessedModelFile, len(details.Files))
-		for j, file := range details.Files {
-			fileType := "other"
-			if file.IsReadme {
-				fileType = "readme"
-			} else if preferredModelFile != nil && file.Path == preferredModelFile.Path {
-				fileType = "model"
-			}
-
-			processedFiles[j] = ProcessedModelFile{
-				Path:     file.Path,
-				Size:     file.Size,
-				SHA256:   file.SHA256,
-				IsReadme: file.IsReadme,
-				FileType: fileType,
-			}
-		}
-
-		processedModel.Files = processedFiles
-
-		// Set preferred model file
-		if preferredModelFile != nil {
-			for _, file := range processedFiles {
-				if file.Path == preferredModelFile.Path {
-					processedModel.PreferredModelFile = &file
-					break
-				}
-			}
-		}
-
-		// Print file information
-		outputBuilder.WriteString(fmt.Sprintf("   Files found: %d\n", len(details.Files)))
-
-		if preferredModelFile != nil {
-			outputBuilder.WriteString(fmt.Sprintf("   Preferred Model File: %s (SHA256: %s)\n",
-				preferredModelFile.Path,
-				preferredModelFile.SHA256))
-		} else {
-			outputBuilder.WriteString(fmt.Sprintf("   No model file found with quantization preferences: %v\n", quantizationPreferences))
-		}
-
-		if details.ReadmeFile != nil {
-			outputBuilder.WriteString(fmt.Sprintf("   README File: %s\n", details.ReadmeFile.Path))
-
-			// Find and set readme file
-			for _, file := range processedFiles {
-				if file.IsReadme {
-					processedModel.ReadmeFile = &file
-					break
-				}
-			}
-
-			fmt.Println("Getting real readme for", model.ModelID, "waiting...")
-			// Use agent to get the real readme and prepare the model description
-			readmeContent, err := getRealReadme(context.Background(), model.ModelID)
-			if err == nil {
-				processedModel.ReadmeContent = readmeContent
-				processedModel.ReadmeContentPreview = truncateString(readmeContent, 200)
-				outputBuilder.WriteString(fmt.Sprintf("   README Content Preview: %s\n",
-					processedModel.ReadmeContentPreview))
-			} else {
-				fmt.Printf("   Warning: Failed to get real readme: %v\n", err)
-			}
-			fmt.Println("Real readme got", readmeContent)
-
-			// Extract metadata (tags, license) from README using LLM
-			fmt.Println("Extracting metadata for", model.ModelID, "waiting...")
-			tags, license, err := extractModelMetadata(context.Background(), processedModel)
-			if err == nil {
-				processedModel.Tags = tags
-				processedModel.License = license
-				outputBuilder.WriteString(fmt.Sprintf("   Tags: %v\n", tags))
-				outputBuilder.WriteString(fmt.Sprintf("   License: %s\n", license))
-			} else {
-				fmt.Printf("   Warning: Failed to extract metadata: %v\n", err)
-			}
-
-			// Extract icon from README or use HuggingFace avatar
-			icon := extractModelIcon(processedModel)
-			if icon != "" {
-				processedModel.Icon = icon
-				outputBuilder.WriteString(fmt.Sprintf("   Icon: %s\n", icon))
-			}
-			// Get README content
-			// readmeContent, err := client.GetReadmeContent(model.ModelID, details.ReadmeFile.Path)
-			// if err == nil {
-			// 	processedModel.ReadmeContent = readmeContent
-			// 	processedModel.ReadmeContentPreview = truncateString(readmeContent, 200)
-			// 	outputBuilder.WriteString(fmt.Sprintf("   README Content Preview: %s\n",
-			// 		processedModel.ReadmeContentPreview))
-			// }
-		}
-
-		// Print all files with their checksums
-		outputBuilder.WriteString("   All Files:\n")
-		for _, file := range processedFiles {
-			outputBuilder.WriteString(fmt.Sprintf("     - %s (%s, %d bytes", file.Path, file.FileType, file.Size))
-			if file.SHA256 != "" {
-				outputBuilder.WriteString(fmt.Sprintf(", SHA256: %s", file.SHA256))
-			}
-			outputBuilder.WriteString(")\n")
-		}
-
-		outputBuilder.WriteString("\n")
-		result.Models = append(result.Models, processedModel)
-	}
-
-	result.FormattedOutput = outputBuilder.String()
-	return result, nil
-}
-
-func truncateString(s string, maxLen int) string {
-	if len(s) <= maxLen {
-		return s
-	}
-	return s[:maxLen] + "..."
-}

.github/gallery-agent/testing.go

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

.github/gallery-agent/tools.go

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

.github/workflows/backend_build.yml

@@ -1,5 +1,5 @@
 ---
-name: 'build backend container images (reusable)'
+name: 'build python backend container images (reusable)'
 
 on:
   workflow_call:
@@ -53,11 +53,6 @@ on:
         description: 'Skip drivers'
         default: 'false'
         type: string
-      ubuntu-version:
-        description: 'Ubuntu version'
-        required: false
-        default: '2204'
-        type: string
     secrets:
       dockerUsername:
         required: false
@@ -102,7 +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'
@@ -213,7 +208,6 @@ jobs:
             CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
             BASE_IMAGE=${{ inputs.base-image }}
             BACKEND=${{ inputs.backend }}
-            UBUNTU_VERSION=${{ inputs.ubuntu-version }}
           context: ${{ inputs.context }}
           file: ${{ inputs.dockerfile }}
           cache-from: type=gha
@@ -234,7 +228,6 @@ jobs:
             CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
             BASE_IMAGE=${{ inputs.base-image }}
             BACKEND=${{ inputs.backend }}
-            UBUNTU_VERSION=${{ inputs.ubuntu-version }}
           context: ${{ inputs.context }}
           file: ${{ inputs.dockerfile }}
           cache-from: type=gha

.github/workflows/backend_build_darwin.yml

@@ -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@v6
+        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@v7
+        uses: actions/download-artifact@v5
         with:
           name: ${{ inputs.backend }}-tar
           path: .

.github/workflows/backend_pr.yml

@@ -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
@@ -52,7 +52,6 @@ jobs:
       dockerfile: ${{ matrix.dockerfile }}
       skip-drivers: ${{ matrix.skip-drivers }}
       context: ${{ matrix.context }}
-      ubuntu-version: ${{ matrix.ubuntu-version }}
     secrets:
       quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
       quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
@@ -70,7 +69,7 @@ jobs:
       tag-suffix: ${{ matrix.tag-suffix }}
       lang: ${{ matrix.lang || 'python' }}
       use-pip: ${{ matrix.backend == 'diffusers' }}
-      runs-on: "macos-latest"
+      runs-on: "macOS-14"
     secrets:
       quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
       quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}

.github/workflows/build-test.yaml

@@ -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@v6
+        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@v6
+        uses: actions/upload-artifact@v4
         with:
           name: launcher-linux
           path: local-ai-launcher-linux.tar.xz

.github/workflows/bump_deps.yaml

@@ -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: |
@@ -49,7 +49,7 @@ jobs:
           rm -rfv ${{ matrix.variable }}_message.txt
           rm -rfv ${{ matrix.variable }}_commit.txt
       - name: Create Pull Request
-        uses: peter-evans/create-pull-request@v8
+        uses: peter-evans/create-pull-request@v7
         with:
           token: ${{ secrets.UPDATE_BOT_TOKEN }}
           push-to-fork: ci-forks/LocalAI

.github/workflows/bump_docs.yaml

@@ -1,10 +1,10 @@
-name: Bump Documentation
+name: Bump dependencies
 on:
   schedule:
     - cron: 0 20 * * *
   workflow_dispatch:
 jobs:
-  bump-docs:
+  bump:
     strategy:
       fail-fast: false
       matrix:
@@ -12,12 +12,12 @@ jobs:
           - repository: "mudler/LocalAI"
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v6
+      - uses: actions/checkout@v5
       - name: Bump dependencies 🔧
         run: |
           bash .github/bump_docs.sh ${{ matrix.repository }}
       - name: Create Pull Request
-        uses: peter-evans/create-pull-request@v8
+        uses: peter-evans/create-pull-request@v7
         with:
           token: ${{ secrets.UPDATE_BOT_TOKEN }}
           push-to-fork: ci-forks/LocalAI

.github/workflows/checksum_checker.yaml

@@ -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
@@ -35,7 +35,7 @@ jobs:
           sudo chmod 777 /hf_cache
           bash .github/checksum_checker.sh gallery/index.yaml
       - name: Create Pull Request
-        uses: peter-evans/create-pull-request@v8
+        uses: peter-evans/create-pull-request@v7
         with:
           token: ${{ secrets.UPDATE_BOT_TOKEN }}
           push-to-fork: ci-forks/LocalAI

.github/workflows/dependabot_auto.yml

@@ -14,13 +14,13 @@ jobs:
     steps:
       - name: Dependabot metadata
         id: metadata
-        uses: dependabot/fetch-metadata@v2.5.0
+        uses: dependabot/fetch-metadata@v2.4.0
         with:
           github-token: "${{ secrets.GITHUB_TOKEN }}"
           skip-commit-verification: true
 
       - name: Checkout repository
-        uses: actions/checkout@v6
+        uses: actions/checkout@v5
 
       - name: Approve a PR if not already approved
         run: |

.github/workflows/deploy-explorer.yaml

@@ -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@v1.2.4
+        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@v1.2.4
+        uses: appleboy/ssh-action@v1.2.2
         with:
             host: ${{ secrets.EXPLORER_SSH_HOST }}
             username: ${{ secrets.EXPLORER_SSH_USERNAME }}

.github/workflows/gallery-agent.yaml

@@ -1,132 +0,0 @@
-name: Gallery Agent
-on:
-
-  schedule:
-    - cron: '0 */3 * * *'  # Run every 4 hours
-  workflow_dispatch:
-    inputs:
-      search_term:
-        description: 'Search term for models'
-        required: false
-        default: 'GGUF'
-        type: string
-      limit:
-        description: 'Maximum number of models to process'
-        required: false
-        default: '15'
-        type: string
-      quantization:
-        description: 'Preferred quantization format'
-        required: false
-        default: 'Q4_K_M'
-        type: string
-      max_models:
-        description: 'Maximum number of models to add to the gallery'
-        required: false
-        default: '1'
-        type: string
-jobs:
-  gallery-agent:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v6
-        with:
-          token: ${{ secrets.GITHUB_TOKEN }}
-
-      - name: Set up Go
-        uses: actions/setup-go@v5
-        with:
-          go-version: '1.21'
-      - name: Proto Dependencies
-        run: |
-          # Install protoc
-          curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
-          unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
-          rm protoc.zip
-          go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
-          go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
-          PATH="$PATH:$HOME/go/bin" make protogen-go
-      - uses: mudler/localai-github-action@v1.1
-        with:
-          model: 'https://huggingface.co/bartowski/Qwen_Qwen3-1.7B-GGUF'
-
-      - name: Run gallery agent
-        env:
-          #OPENAI_MODEL: ${{ secrets.OPENAI_MODEL }}
-          OPENAI_MODE: Qwen_Qwen3-1.7B-GGUF
-          OPENAI_BASE_URL: "http://localhost:8080"
-          OPENAI_KEY: ${{ secrets.OPENAI_KEY }}
-          #OPENAI_BASE_URL: ${{ secrets.OPENAI_BASE_URL }}
-          SEARCH_TERM: ${{ github.event.inputs.search_term || 'GGUF' }}
-          LIMIT: ${{ github.event.inputs.limit || '15' }}
-          QUANTIZATION: ${{ github.event.inputs.quantization || 'Q4_K_M' }}
-          MAX_MODELS: ${{ github.event.inputs.max_models || '1' }}
-        run: |
-          export GALLERY_INDEX_PATH=$PWD/gallery/index.yaml
-          go run ./.github/gallery-agent
-
-      - name: Check for changes
-        id: check_changes
-        run: |
-          if git diff --quiet gallery/index.yaml; then
-            echo "changes=false" >> $GITHUB_OUTPUT
-            echo "No changes detected in gallery/index.yaml"
-          else
-            echo "changes=true" >> $GITHUB_OUTPUT
-            echo "Changes detected in gallery/index.yaml"
-            git diff gallery/index.yaml
-          fi
-
-      - name: Read gallery agent summary
-        id: read_summary
-        if: steps.check_changes.outputs.changes == 'true'
-        run: |
-          if [ -f "./gallery-agent-summary.json" ]; then
-            echo "summary_exists=true" >> $GITHUB_OUTPUT
-            # Extract summary data using jq
-            echo "search_term=$(jq -r '.search_term' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
-            echo "total_found=$(jq -r '.total_found' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
-            echo "models_added=$(jq -r '.models_added' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
-            echo "quantization=$(jq -r '.quantization' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
-            echo "processing_time=$(jq -r '.processing_time' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
-            
-            # Create a formatted list of added models with URLs
-            added_models=$(jq -r 'range(0; .added_model_ids | length) as $i | "- [\(.added_model_ids[$i])](\(.added_model_urls[$i]))"' ./gallery-agent-summary.json | tr '\n' '\n')
-            echo "added_models<<EOF" >> $GITHUB_OUTPUT
-            echo "$added_models" >> $GITHUB_OUTPUT
-            echo "EOF" >> $GITHUB_OUTPUT
-            rm -f ./gallery-agent-summary.json
-          else
-            echo "summary_exists=false" >> $GITHUB_OUTPUT
-          fi
-
-      - name: Create Pull Request
-        if: steps.check_changes.outputs.changes == 'true'
-        uses: peter-evans/create-pull-request@v8
-        with:
-          token: ${{ secrets.UPDATE_BOT_TOKEN }}
-          push-to-fork: ci-forks/LocalAI
-          commit-message: 'chore(model gallery): :robot: add new models via gallery agent'
-          title: 'chore(model gallery): :robot: add ${{ steps.read_summary.outputs.models_added || 0 }} new models via gallery agent'
-          # Branch has to be unique so PRs are not overriding each other
-          branch-suffix: timestamp
-          body: |
-            This PR was automatically created by the gallery agent workflow.
-            
-            **Summary:**
-            - **Search Term:** ${{ steps.read_summary.outputs.search_term || github.event.inputs.search_term || 'GGUF' }}
-            - **Models Found:** ${{ steps.read_summary.outputs.total_found || 'N/A' }}
-            - **Models Added:** ${{ steps.read_summary.outputs.models_added || '0' }}
-            - **Quantization:** ${{ steps.read_summary.outputs.quantization || github.event.inputs.quantization || 'Q4_K_M' }}
-            - **Processing Time:** ${{ steps.read_summary.outputs.processing_time || 'N/A' }}
-            
-            **Added Models:**
-            ${{ steps.read_summary.outputs.added_models || '- No models added' }}
-            
-            **Workflow Details:**
-            - Triggered by: `${{ github.event_name }}`
-            - Run ID: `${{ github.run_id }}`
-            - Commit: `${{ github.sha }}`
-          signoff: true
-          delete-branch: true

.github/workflows/generate_grpc_cache.yaml

@@ -16,7 +16,7 @@ jobs:
     strategy:
       matrix:
         include:
-          - grpc-base-image: ubuntu:24.04
+          - grpc-base-image: ubuntu:22.04
             runs-on: 'ubuntu-latest'
             platforms: 'linux/amd64,linux/arm64'
     runs-on: ${{matrix.runs-on}}
@@ -73,7 +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

.github/workflows/generate_intel_image.yaml

@@ -15,8 +15,8 @@ jobs:
     strategy:
       matrix:
         include:
-          - base-image: intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04
-            runs-on: 'arc-runner-set'
+          - base-image: intel/oneapi-basekit:2025.2.0-0-devel-ubuntu22.04
+            runs-on: 'ubuntu-latest'
             platforms: 'linux/amd64'
     runs-on: ${{matrix.runs-on}}
     steps:
@@ -43,7 +43,7 @@ jobs:
         uses: docker/setup-buildx-action@master
 
       - name: Checkout
-        uses: actions/checkout@v6
+        uses: actions/checkout@v5
 
       - name: Cache Intel images
         uses: docker/build-push-action@v6
@@ -53,7 +53,7 @@ jobs:
             BASE_IMAGE=${{ matrix.base-image }}
           context: .
           file: ./Dockerfile
-          tags: quay.io/go-skynet/intel-oneapi-base:24.04
+          tags: quay.io/go-skynet/intel-oneapi-base:latest
           push: true
           target: intel
           platforms: ${{ matrix.platforms }}

.github/workflows/image-pr.yml

@@ -1,95 +1,77 @@
 ---
-  name: 'build container images tests'
-  
-  on:
-    pull_request:
-  
-  concurrency:
-    group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
-    cancel-in-progress: true
-  
-  jobs:
-    image-build:
-      uses: ./.github/workflows/image_build.yml
-      with:
-        tag-latest: ${{ matrix.tag-latest }}
-        tag-suffix: ${{ matrix.tag-suffix }}
-        build-type: ${{ matrix.build-type }}
-        cuda-major-version: ${{ matrix.cuda-major-version }}
-        cuda-minor-version: ${{ matrix.cuda-minor-version }}
-        platforms: ${{ matrix.platforms }}
-        runs-on: ${{ matrix.runs-on }}
-        base-image: ${{ matrix.base-image }}
-        grpc-base-image: ${{ matrix.grpc-base-image }}
-        makeflags: ${{ matrix.makeflags }}
-        ubuntu-version: ${{ matrix.ubuntu-version }}
-      secrets:
-        dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
-        dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
-        quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
-        quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
-      strategy:
-        # Pushing with all jobs in parallel
-        # eats the bandwidth of all the nodes
-        max-parallel: ${{ github.event_name != 'pull_request' && 4 || 8 }}
-        fail-fast: false
-        matrix:
-          include:
-            - build-type: 'cublas'
-              cuda-major-version: "12"
-              cuda-minor-version: "8"
-              platforms: 'linux/amd64'
-              tag-latest: 'false'
-              tag-suffix: '-gpu-nvidia-cuda-12'
-              runs-on: 'ubuntu-latest'
-              base-image: "ubuntu:24.04"
-              makeflags: "--jobs=3 --output-sync=target"
-              ubuntu-version: '2404'
-            - build-type: 'cublas'
-              cuda-major-version: "13"
-              cuda-minor-version: "0"
-              platforms: 'linux/amd64'
-              tag-latest: 'false'
-              tag-suffix: '-gpu-nvidia-cuda-13'
-              runs-on: 'ubuntu-latest'
-              base-image: "ubuntu:22.04"
-              makeflags: "--jobs=3 --output-sync=target"
-              ubuntu-version: '2404'
-            - build-type: 'hipblas'
-              platforms: 'linux/amd64'
-              tag-latest: 'false'
-              tag-suffix: '-hipblas'
-              base-image: "rocm/dev-ubuntu-24.04:6.4.4"
-              grpc-base-image: "ubuntu:24.04"
-              runs-on: 'ubuntu-latest'
-              makeflags: "--jobs=3 --output-sync=target"
-              ubuntu-version: '2404'
-            - build-type: 'sycl'
-              platforms: 'linux/amd64'
-              tag-latest: 'false'
-              base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
-              grpc-base-image: "ubuntu:24.04"
-              tag-suffix: 'sycl'
-              runs-on: 'ubuntu-latest'
-              makeflags: "--jobs=3 --output-sync=target"
-              ubuntu-version: '2404'
-            - build-type: 'vulkan'
-              platforms: 'linux/amd64,linux/arm64'
-              tag-latest: 'false'
-              tag-suffix: '-vulkan-core'
-              runs-on: 'ubuntu-latest'
-              base-image: "ubuntu:24.04"
-              makeflags: "--jobs=4 --output-sync=target"
-              ubuntu-version: '2404'
-            - build-type: 'cublas'
-              cuda-major-version: "13"
-              cuda-minor-version: "0"
-              platforms: 'linux/arm64'
-              tag-latest: 'false'
-              tag-suffix: '-nvidia-l4t-arm64-cuda-13'
-              base-image: "ubuntu:24.04"
-              runs-on: 'ubuntu-24.04-arm'
-              makeflags: "--jobs=4 --output-sync=target"
-              skip-drivers: 'false'
-              ubuntu-version: '2404'
-  
+name: 'build container images tests'
+
+on:
+  pull_request:
+
+concurrency:
+  group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
+  cancel-in-progress: true
+
+jobs:
+  image-build:
+    uses: ./.github/workflows/image_build.yml
+    with:
+      tag-latest: ${{ matrix.tag-latest }}
+      tag-suffix: ${{ matrix.tag-suffix }}
+      build-type: ${{ matrix.build-type }}
+      cuda-major-version: ${{ matrix.cuda-major-version }}
+      cuda-minor-version: ${{ matrix.cuda-minor-version }}
+      platforms: ${{ matrix.platforms }}
+      runs-on: ${{ matrix.runs-on }}
+      base-image: ${{ matrix.base-image }}
+      grpc-base-image: ${{ matrix.grpc-base-image }}
+      makeflags: ${{ matrix.makeflags }}
+    secrets:
+      dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+      dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+    strategy:
+      # Pushing with all jobs in parallel
+      # eats the bandwidth of all the nodes
+      max-parallel: ${{ github.event_name != 'pull_request' && 4 || 8 }}
+      fail-fast: false
+      matrix:
+        include:
+          - build-type: 'cublas'
+            cuda-major-version: "13"
+            cuda-minor-version: "0"
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-gpu-nvidia-cuda-13'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
+            makeflags: "--jobs=3 --output-sync=target"
+          - build-type: 'cublas'
+            cuda-major-version: "12"
+            cuda-minor-version: "0"
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-gpu-nvidia-cuda-12'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
+            makeflags: "--jobs=3 --output-sync=target"
+          - build-type: 'hipblas'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-hipblas'
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
+            grpc-base-image: "ubuntu:22.04"
+            runs-on: 'ubuntu-latest'
+            makeflags: "--jobs=3 --output-sync=target"
+          - build-type: 'sycl'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
+            grpc-base-image: "ubuntu:22.04"
+            tag-suffix: 'sycl'
+            runs-on: 'ubuntu-latest'
+            makeflags: "--jobs=3 --output-sync=target"
+          - build-type: 'vulkan'
+            platforms: 'linux/amd64'
+            tag-latest: 'false'
+            tag-suffix: '-vulkan-core'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
+            makeflags: "--jobs=4 --output-sync=target"

.github/workflows/image.yml

@@ -1,187 +1,165 @@
 ---
-  name: 'build container images'
-  
-  on:
-    push:
-      branches:
-        - master
-      tags:
-        - '*'
-  
-  concurrency:
-    group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
-    cancel-in-progress: true
-  
-  jobs:
-    hipblas-jobs:
-      uses: ./.github/workflows/image_build.yml
-      with:
-        tag-latest: ${{ matrix.tag-latest }}
-        tag-suffix: ${{ matrix.tag-suffix }}
-        build-type: ${{ matrix.build-type }}
-        cuda-major-version: ${{ matrix.cuda-major-version }}
-        cuda-minor-version: ${{ matrix.cuda-minor-version }}
-        platforms: ${{ matrix.platforms }}
-        runs-on: ${{ matrix.runs-on }}
-        base-image: ${{ matrix.base-image }}
-        grpc-base-image: ${{ matrix.grpc-base-image }}
-        aio: ${{ matrix.aio }}
-        makeflags: ${{ matrix.makeflags }}
-        ubuntu-version: ${{ matrix.ubuntu-version }}
-        ubuntu-codename: ${{ matrix.ubuntu-codename }}
-      secrets:
-        dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
-        dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
-        quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
-        quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
-      strategy:
-        matrix:
-          include:
-            - build-type: 'hipblas'
-              platforms: 'linux/amd64'
-              tag-latest: 'auto'
-              tag-suffix: '-gpu-hipblas'
-              base-image: "rocm/dev-ubuntu-24.04:6.4.4"
-              grpc-base-image: "ubuntu:24.04"
-              runs-on: 'ubuntu-latest'
-              makeflags: "--jobs=3 --output-sync=target"
-              aio: "-aio-gpu-hipblas"
-              ubuntu-version: '2404'
-              ubuntu-codename: 'noble'
-  
-    core-image-build:
-      uses: ./.github/workflows/image_build.yml
-      with:
-        tag-latest: ${{ matrix.tag-latest }}
-        tag-suffix: ${{ matrix.tag-suffix }}
-        build-type: ${{ matrix.build-type }}
-        cuda-major-version: ${{ matrix.cuda-major-version }}
-        cuda-minor-version: ${{ matrix.cuda-minor-version }}
-        platforms: ${{ matrix.platforms }}
-        runs-on: ${{ matrix.runs-on }}
-        aio: ${{ matrix.aio }}
-        base-image: ${{ matrix.base-image }}
-        grpc-base-image: ${{ matrix.grpc-base-image }}
-        makeflags: ${{ matrix.makeflags }}
-        skip-drivers: ${{ matrix.skip-drivers }}
-        ubuntu-version: ${{ matrix.ubuntu-version }}
-        ubuntu-codename: ${{ matrix.ubuntu-codename }}
-      secrets:
-        dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
-        dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
-        quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
-        quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
-      strategy:
-        #max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
-        matrix:
-          include:
-            - build-type: ''
-              platforms: 'linux/amd64,linux/arm64'
-              tag-latest: 'auto'
-              tag-suffix: ''
-              base-image: "ubuntu:24.04"
-              runs-on: 'ubuntu-latest'
-              aio: "-aio-cpu"
-              makeflags: "--jobs=4 --output-sync=target"
-              skip-drivers: 'false'
-              ubuntu-version: '2404'
-              ubuntu-codename: 'noble'
-            - build-type: 'cublas'
-              cuda-major-version: "12"
-              cuda-minor-version: "8"
-              platforms: 'linux/amd64'
-              tag-latest: 'auto'
-              tag-suffix: '-gpu-nvidia-cuda-12'
-              runs-on: 'ubuntu-latest'
-              base-image: "ubuntu:24.04"
-              skip-drivers: 'false'
-              makeflags: "--jobs=4 --output-sync=target"
-              aio: "-aio-gpu-nvidia-cuda-12"
-              ubuntu-version: '2404'
-              ubuntu-codename: 'noble'
-            - build-type: 'cublas'
-              cuda-major-version: "13"
-              cuda-minor-version: "0"
-              platforms: 'linux/amd64'
-              tag-latest: 'auto'
-              tag-suffix: '-gpu-nvidia-cuda-13'
-              runs-on: 'ubuntu-latest'
-              base-image: "ubuntu:22.04"
-              skip-drivers: 'false'
-              makeflags: "--jobs=4 --output-sync=target"
-              aio: "-aio-gpu-nvidia-cuda-13"
-              ubuntu-version: '2404'
-              ubuntu-codename: 'noble'
-            - build-type: 'vulkan'
-              platforms: 'linux/amd64,linux/arm64'
-              tag-latest: 'auto'
-              tag-suffix: '-gpu-vulkan'
-              runs-on: 'ubuntu-latest'
-              base-image: "ubuntu:24.04"
-              skip-drivers: 'false'
-              makeflags: "--jobs=4 --output-sync=target"
-              aio: "-aio-gpu-vulkan"
-              ubuntu-version: '2404'
-              ubuntu-codename: 'noble'
-            - build-type: 'intel'
-              platforms: 'linux/amd64'
-              tag-latest: 'auto'
-              base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
-              grpc-base-image: "ubuntu:24.04"
-              tag-suffix: '-gpu-intel'
-              runs-on: 'ubuntu-latest'
-              makeflags: "--jobs=3 --output-sync=target"
-              aio: "-aio-gpu-intel"
-              ubuntu-version: '2404'
-              ubuntu-codename: 'noble'
-  
-    gh-runner:
-      uses: ./.github/workflows/image_build.yml
-      with:
-        tag-latest: ${{ matrix.tag-latest }}
-        tag-suffix: ${{ matrix.tag-suffix }}
-        build-type: ${{ matrix.build-type }}
-        cuda-major-version: ${{ matrix.cuda-major-version }}
-        cuda-minor-version: ${{ matrix.cuda-minor-version }}
-        platforms: ${{ matrix.platforms }}
-        runs-on: ${{ matrix.runs-on }}
-        aio: ${{ matrix.aio }}
-        base-image: ${{ matrix.base-image }}
-        grpc-base-image: ${{ matrix.grpc-base-image }}
-        makeflags: ${{ matrix.makeflags }}
-        skip-drivers: ${{ matrix.skip-drivers }}
-        ubuntu-version: ${{ matrix.ubuntu-version }}
-        ubuntu-codename: ${{ matrix.ubuntu-codename }}
-      secrets:
-        dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
-        dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
-        quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
-        quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
-      strategy:
-        matrix:
-          include:
-            - build-type: 'cublas'
-              cuda-major-version: "12"
-              cuda-minor-version: "0"
-              platforms: 'linux/arm64'
-              tag-latest: 'auto'
-              tag-suffix: '-nvidia-l4t-arm64'
-              base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
-              runs-on: 'ubuntu-24.04-arm'
-              makeflags: "--jobs=4 --output-sync=target"
-              skip-drivers: 'true'
-              ubuntu-version: "2204"
-              ubuntu-codename: 'jammy'
-            - build-type: 'cublas'
-              cuda-major-version: "13"
-              cuda-minor-version: "0"
-              platforms: 'linux/arm64'
-              tag-latest: 'auto'
-              tag-suffix: '-nvidia-l4t-arm64-cuda-13'
-              base-image: "ubuntu:24.04"
-              runs-on: 'ubuntu-24.04-arm'
-              makeflags: "--jobs=4 --output-sync=target"
-              skip-drivers: 'false'
-              ubuntu-version: '2404'
-              ubuntu-codename: 'noble'
-  
+name: 'build container images'
+
+on:
+  push:
+    branches:
+      - master
+    tags:
+      - '*'
+
+concurrency:
+  group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
+  cancel-in-progress: true
+
+jobs:
+  hipblas-jobs:
+    uses: ./.github/workflows/image_build.yml
+    with:
+      tag-latest: ${{ matrix.tag-latest }}
+      tag-suffix: ${{ matrix.tag-suffix }}
+      build-type: ${{ matrix.build-type }}
+      cuda-major-version: ${{ matrix.cuda-major-version }}
+      cuda-minor-version: ${{ matrix.cuda-minor-version }}
+      platforms: ${{ matrix.platforms }}
+      runs-on: ${{ matrix.runs-on }}
+      base-image: ${{ matrix.base-image }}
+      grpc-base-image: ${{ matrix.grpc-base-image }}
+      aio: ${{ matrix.aio }}
+      makeflags: ${{ matrix.makeflags }}
+    secrets:
+      dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+      dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+    strategy:
+      matrix:
+        include:
+          - build-type: 'hipblas'
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-hipblas'
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
+            grpc-base-image: "ubuntu:22.04"
+            runs-on: 'ubuntu-latest'
+            makeflags: "--jobs=3 --output-sync=target"
+            aio: "-aio-gpu-hipblas"
+
+  core-image-build:
+    uses: ./.github/workflows/image_build.yml
+    with:
+      tag-latest: ${{ matrix.tag-latest }}
+      tag-suffix: ${{ matrix.tag-suffix }}
+      build-type: ${{ matrix.build-type }}
+      cuda-major-version: ${{ matrix.cuda-major-version }}
+      cuda-minor-version: ${{ matrix.cuda-minor-version }}
+      platforms: ${{ matrix.platforms }}
+      runs-on: ${{ matrix.runs-on }}
+      aio: ${{ matrix.aio }}
+      base-image: ${{ matrix.base-image }}
+      grpc-base-image: ${{ matrix.grpc-base-image }}
+      makeflags: ${{ matrix.makeflags }}
+      skip-drivers: ${{ matrix.skip-drivers }}
+    secrets:
+      dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+      dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+    strategy:
+      #max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
+      matrix:
+        include:
+          - build-type: ''
+            platforms: 'linux/amd64,linux/arm64'
+            tag-latest: 'auto'
+            tag-suffix: ''
+            base-image: "ubuntu:22.04"
+            runs-on: 'ubuntu-latest'
+            aio: "-aio-cpu"
+            makeflags: "--jobs=4 --output-sync=target"
+            skip-drivers: 'false'
+          - build-type: 'cublas'
+            cuda-major-version: "11"
+            cuda-minor-version: "7"
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-nvidia-cuda-11'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
+            makeflags: "--jobs=4 --output-sync=target"
+            skip-drivers: 'false'
+            aio: "-aio-gpu-nvidia-cuda-11"
+          - build-type: 'cublas'
+            cuda-major-version: "12"
+            cuda-minor-version: "0"
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-nvidia-cuda-12'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
+            skip-drivers: 'false'
+            makeflags: "--jobs=4 --output-sync=target"
+            aio: "-aio-gpu-nvidia-cuda-12"
+          - build-type: 'cublas'
+            cuda-major-version: "13"
+            cuda-minor-version: "0"
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-nvidia-cuda-13'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
+            skip-drivers: 'false'
+            makeflags: "--jobs=4 --output-sync=target"
+            aio: "-aio-gpu-nvidia-cuda-13"
+          - build-type: 'vulkan'
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-vulkan'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
+            skip-drivers: 'false'
+            makeflags: "--jobs=4 --output-sync=target"
+            aio: "-aio-gpu-vulkan"
+          - build-type: 'intel'
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
+            grpc-base-image: "ubuntu:22.04"
+            tag-suffix: '-gpu-intel'
+            runs-on: 'ubuntu-latest'
+            makeflags: "--jobs=3 --output-sync=target"
+            aio: "-aio-gpu-intel"
+
+  gh-runner:
+    uses: ./.github/workflows/image_build.yml
+    with:
+      tag-latest: ${{ matrix.tag-latest }}
+      tag-suffix: ${{ matrix.tag-suffix }}
+      build-type: ${{ matrix.build-type }}
+      cuda-major-version: ${{ matrix.cuda-major-version }}
+      cuda-minor-version: ${{ matrix.cuda-minor-version }}
+      platforms: ${{ matrix.platforms }}
+      runs-on: ${{ matrix.runs-on }}
+      aio: ${{ matrix.aio }}
+      base-image: ${{ matrix.base-image }}
+      grpc-base-image: ${{ matrix.grpc-base-image }}
+      makeflags: ${{ matrix.makeflags }}
+      skip-drivers: ${{ matrix.skip-drivers }}
+    secrets:
+      dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+      dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+    strategy:
+      matrix:
+        include:
+          - build-type: 'cublas'
+            cuda-major-version: "12"
+            cuda-minor-version: "0"
+            platforms: 'linux/arm64'
+            tag-latest: 'auto'
+            tag-suffix: '-nvidia-l4t-arm64'
+            base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
+            runs-on: 'ubuntu-24.04-arm'
+            makeflags: "--jobs=4 --output-sync=target"
+            skip-drivers: 'true'

.github/workflows/image_build.yml

@@ -23,7 +23,7 @@ on:
         type: string
       cuda-minor-version:
         description: 'CUDA minor version'
-        default: "9"
+        default: "4"
         type: string
       platforms:
         description: 'Platforms'
@@ -56,16 +56,6 @@ on:
         required: false
         default: ''
         type: string
-      ubuntu-version:
-        description: 'Ubuntu version'
-        required: false
-        default: '2204'
-        type: string
-      ubuntu-codename:
-        description: 'Ubuntu codename'
-        required: false
-        default: 'noble'
-        type: string
     secrets:
       dockerUsername:
         required: true
@@ -104,7 +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'
@@ -248,8 +238,6 @@ jobs:
             GRPC_VERSION=v1.65.0
             MAKEFLAGS=${{ inputs.makeflags }}
             SKIP_DRIVERS=${{ inputs.skip-drivers }}
-            UBUNTU_VERSION=${{ inputs.ubuntu-version }}
-            UBUNTU_CODENAME=${{ inputs.ubuntu-codename }}
           context: .
           file: ./Dockerfile
           cache-from: type=gha
@@ -277,8 +265,6 @@ jobs:
             GRPC_VERSION=v1.65.0
             MAKEFLAGS=${{ inputs.makeflags }}
             SKIP_DRIVERS=${{ inputs.skip-drivers }}
-            UBUNTU_VERSION=${{ inputs.ubuntu-version }}
-            UBUNTU_CODENAME=${{ inputs.ubuntu-codename }}
           context: .
           file: ./Dockerfile
           cache-from: type=gha

.github/workflows/localaibot_automerge.yml

@@ -6,15 +6,14 @@ permissions:
   contents: write
   pull-requests: write
   packages: read
-  issues: write # for Homebrew/actions/post-comment
-  actions: write # to dispatch publish workflow
+
 jobs:
   dependabot:
     runs-on: ubuntu-latest
-    if: ${{ github.actor == 'localai-bot' && !contains(github.event.pull_request.title, 'chore(model gallery):') }}
+    if: ${{ github.actor == 'localai-bot' }}
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v6
+        uses: actions/checkout@v5
 
       - name: Approve a PR if not already approved
         run: |

.github/workflows/notify-models.yaml

@@ -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

.github/workflows/notify-releases.yaml

@@ -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: |

.github/workflows/release.yaml

@@ -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

.github/workflows/secscan.yaml

@@ -14,17 +14,17 @@ 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]' }}
-        uses: securego/gosec@v2.22.9
+        uses: securego/gosec@v2.22.8
         with:
           # we let the report trigger content trigger a failure using the GitHub Security features.
           args: '-no-fail -fmt sarif -out results.sarif ./...'
       - name: Upload SARIF file
         if: ${{ github.actor != 'dependabot[bot]' }}
-        uses: github/codeql-action/upload-sarif@v4
+        uses: github/codeql-action/upload-sarif@v3
         with:
           # Path to SARIF file relative to the root of the repository
           sarif_file: results.sarif

.github/workflows/stalebot.yml

@@ -10,7 +10,7 @@ jobs:
   stale:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/stale@997185467fa4f803885201cee163a9f38240193d # 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.'

.github/workflows/test-extra.yml

@@ -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
@@ -232,13 +232,13 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Clone
-        uses: actions/checkout@v6
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Dependencies
         run: |
           sudo apt-get update
-          sudo apt-get install -y build-essential ffmpeg
+          sudo apt-get install build-essential ffmpeg
           sudo apt-get install -y ca-certificates cmake curl patch espeak espeak-ng python3-pip
           # Install UV
           curl -LsSf https://astral.sh/uv/install.sh | sh
@@ -247,98 +247,3 @@ jobs:
         run: |
           make --jobs=5 --output-sync=target -C backend/python/coqui
           make --jobs=5 --output-sync=target -C backend/python/coqui test
-  tests-moonshine:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Clone
-        uses: actions/checkout@v6
-        with:
-          submodules: true
-      - name: Dependencies
-        run: |
-          sudo apt-get update
-          sudo apt-get install -y build-essential ffmpeg
-          sudo apt-get install -y ca-certificates cmake curl patch python3-pip
-          # Install UV
-          curl -LsSf https://astral.sh/uv/install.sh | sh
-          pip install --user --no-cache-dir grpcio-tools==1.64.1
-      - name: Test moonshine
-        run: |
-          make --jobs=5 --output-sync=target -C backend/python/moonshine
-          make --jobs=5 --output-sync=target -C backend/python/moonshine test
-  tests-pocket-tts:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Clone
-        uses: actions/checkout@v6
-        with:
-          submodules: true
-      - name: Dependencies
-        run: |
-          sudo apt-get update
-          sudo apt-get install -y build-essential ffmpeg
-          sudo apt-get install -y ca-certificates cmake curl patch python3-pip
-          # Install UV
-          curl -LsSf https://astral.sh/uv/install.sh | sh
-          pip install --user --no-cache-dir grpcio-tools==1.64.1
-      - name: Test pocket-tts
-        run: |
-          make --jobs=5 --output-sync=target -C backend/python/pocket-tts
-          make --jobs=5 --output-sync=target -C backend/python/pocket-tts test
-  tests-qwen-tts:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Clone
-        uses: actions/checkout@v6
-        with:
-          submodules: true
-      - name: Dependencies
-        run: |
-          sudo apt-get update
-          sudo apt-get install -y build-essential ffmpeg
-          sudo apt-get install -y ca-certificates cmake curl patch python3-pip
-          # Install UV
-          curl -LsSf https://astral.sh/uv/install.sh | sh
-          pip install --user --no-cache-dir grpcio-tools==1.64.1
-      - name: Test qwen-tts
-        run: |
-          make --jobs=5 --output-sync=target -C backend/python/qwen-tts
-          make --jobs=5 --output-sync=target -C backend/python/qwen-tts test
-  tests-qwen-asr:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Clone
-        uses: actions/checkout@v6
-        with:
-          submodules: true
-      - name: Dependencies
-        run: |
-          sudo apt-get update
-          sudo apt-get install -y build-essential ffmpeg sox
-          sudo apt-get install -y ca-certificates cmake curl patch python3-pip
-          # Install UV
-          curl -LsSf https://astral.sh/uv/install.sh | sh
-          pip install --user --no-cache-dir grpcio-tools==1.64.1
-      - name: Test qwen-asr
-        run: |
-          make --jobs=5 --output-sync=target -C backend/python/qwen-asr
-          make --jobs=5 --output-sync=target -C backend/python/qwen-asr test
-  tests-voxcpm:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Clone
-        uses: actions/checkout@v6
-        with:
-          submodules: true
-      - name: Dependencies
-        run: |
-          sudo apt-get update
-          sudo apt-get install build-essential ffmpeg
-          sudo apt-get install -y ca-certificates cmake curl patch python3-pip
-          # Install UV
-          curl -LsSf https://astral.sh/uv/install.sh | sh
-          pip install --user --no-cache-dir grpcio-tools==1.64.1
-      - name: Test voxcpm
-        run: |
-          make --jobs=5 --output-sync=target -C backend/python/voxcpm
-          make --jobs=5 --output-sync=target -C backend/python/voxcpm test

.github/workflows/test.yml

@@ -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 ${{ matrix.go-version }}
@@ -109,6 +109,11 @@ jobs:
           sudo apt-get update
           sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
           export CUDACXX=/usr/local/cuda/bin/nvcc
+
+
+          # The python3-grpc-tools package in 22.04 is too old
+          pip install --user grpcio-tools==1.71.0 grpcio==1.71.0
+
           make -C backend/python/transformers
 
           make backends/huggingface backends/llama-cpp backends/local-store backends/silero-vad backends/piper backends/whisper backends/stablediffusion-ggml
@@ -119,7 +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: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.23
+        uses: mxschmitt/action-tmate@v3.22
         with:
           detached: true
           connect-timeout-seconds: 180
@@ -161,7 +166,7 @@ jobs:
           sudo rm -rfv build || true
           df -h
       - name: Clone
-        uses: actions/checkout@v6
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Dependencies
@@ -178,20 +183,20 @@ jobs:
             PATH="$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
           limit-access-to-actor: true
 
   tests-apple:
-    runs-on: macos-latest
+    runs-on: macOS-14
     strategy:
       matrix:
-        go-version: ['1.25.x']
+        go-version: ['1.21.x']
     steps:
       - name: Clone
-        uses: actions/checkout@v6
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Setup Go ${{ matrix.go-version }}
@@ -205,7 +210,7 @@ jobs:
       - name: Dependencies
         run: |
           brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm
-          pip install --user --no-cache-dir grpcio-tools grpcio
+          pip install --user --no-cache-dir grpcio-tools==1.71.0 grpcio==1.71.0
       - name: Build llama-cpp-darwin
         run: |
           make protogen-go
@@ -221,7 +226,7 @@ jobs:
           PATH="$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

.github/workflows/tests-e2e.yml

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

.github/workflows/update_swagger.yaml

@@ -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'
@@ -25,7 +25,7 @@ jobs:
         run: |
           make protogen-go swagger
       - name: Create Pull Request
-        uses: peter-evans/create-pull-request@v8
+        uses: peter-evans/create-pull-request@v7
         with:
           token: ${{ secrets.UPDATE_BOT_TOKEN }}
           push-to-fork: ci-forks/LocalAI

.gitignore

@@ -25,7 +25,6 @@ go-bert
 # LocalAI build binary
 LocalAI
 /local-ai
-/local-ai-launcher
 # prevent above rules from omitting the helm chart
 !charts/*
 # prevent above rules from omitting the api/localai folder
@@ -36,8 +35,6 @@ LocalAI
 models/*
 test-models/
 test-dir/
-tests/e2e-aio/backends
-tests/e2e-aio/models
 
 release/
 

.gitmodules

@@ -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

.goreleaser.yaml

@@ -22,9 +22,6 @@ builds:
     goarch:
       - amd64
       - arm64
-    ignore:
-      - goos: darwin
-        goarch: amd64
 archives:
   - formats: [ 'binary' ] # this removes the tar of the archives, leaving the binaries alone
     name_template: local-ai-{{ .Tag }}-{{ .Os }}-{{ .Arch }}{{ if .Arm }}v{{ .Arm }}{{ end }}

AGENTS.md

@@ -1,290 +0,0 @@
-# Build and testing
-
-Building and testing the project depends on the components involved and the platform where development is taking place. Due to the amount of context required it's usually best not to try building or testing the project unless the user requests it. If you must build the project then inspect the Makefile in the project root and the Makefiles of any backends that are effected by changes you are making. In addition the workflows in .github/workflows can be used as a reference when it is unclear how to build or test a component. The primary Makefile contains targets for building inside or outside Docker, if the user has not previously specified a preference then ask which they would like to use.
-
-## Building a specified backend
-
-Let's say the user wants to build a particular backend for a given platform. For example let's say they want to build coqui for ROCM/hipblas
-
-- The Makefile has targets like `docker-build-coqui` created with `generate-docker-build-target` at the time of writing. Recently added backends may require a new target.
-- At a minimum we need to set the BUILD_TYPE, BASE_IMAGE build-args
-  - Use .github/workflows/backend.yml as a reference it lists the needed args in the `include` job strategy matrix
-  - l4t and cublas also requires the CUDA major and minor version
-- You can pretty print a command like `DOCKER_MAKEFLAGS=-j$(nproc --ignore=1) BUILD_TYPE=hipblas BASE_IMAGE=rocm/dev-ubuntu-24.04:6.4.4 make docker-build-coqui`
-- Unless the user specifies that they want you to run the command, then just print it because not all agent frontends handle long running jobs well and the output may overflow your context
-- The user may say they want to build AMD or ROCM instead of hipblas, or Intel instead of SYCL or NVIDIA insted of l4t or cublas. Ask for confirmation if there is ambiguity.
-- Sometimes the user may need extra parameters to be added to `docker build` (e.g. `--platform` for cross-platform builds or `--progress` to view the full logs), in which case you can generate the `docker build` command directly.
-
-## Adding a New Backend
-
-When adding a new backend to LocalAI, you need to update several files to ensure the backend is properly built, tested, and registered. Here's a step-by-step guide based on the pattern used for adding backends like `moonshine`:
-
-### 1. Create Backend Directory Structure
-
-Create the backend directory under the appropriate location:
-- **Python backends**: `backend/python/<backend-name>/`
-- **Go backends**: `backend/go/<backend-name>/`
-- **C++ backends**: `backend/cpp/<backend-name>/`
-
-For Python backends, you'll typically need:
-- `backend.py` - Main gRPC server implementation
-- `Makefile` - Build configuration
-- `install.sh` - Installation script for dependencies
-- `protogen.sh` - Protocol buffer generation script
-- `requirements.txt` - Python dependencies
-- `run.sh` - Runtime script
-- `test.py` / `test.sh` - Test files
-
-### 2. Add Build Configurations to `.github/workflows/backend.yml`
-
-Add build matrix entries for each platform/GPU type you want to support. Look at similar backends (e.g., `chatterbox`, `faster-whisper`) for reference.
-
-**Placement in file:**
-- CPU builds: Add after other CPU builds (e.g., after `cpu-chatterbox`)
-- CUDA 12 builds: Add after other CUDA 12 builds (e.g., after `gpu-nvidia-cuda-12-chatterbox`)
-- CUDA 13 builds: Add after other CUDA 13 builds (e.g., after `gpu-nvidia-cuda-13-chatterbox`)
-
-**Additional build types you may need:**
-- ROCm/HIP: Use `build-type: 'hipblas'` with `base-image: "rocm/dev-ubuntu-24.04:6.4.4"`
-- Intel/SYCL: Use `build-type: 'intel'` or `build-type: 'sycl_f16'`/`sycl_f32` with `base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"`
-- L4T (ARM): Use `build-type: 'l4t'` with `platforms: 'linux/arm64'` and `runs-on: 'ubuntu-24.04-arm'`
-
-### 3. Add Backend Metadata to `backend/index.yaml`
-
-**Step 3a: Add Meta Definition**
-
-Add a YAML anchor definition in the `## metas` section (around line 2-300). Look for similar backends to use as a template such as `diffusers` or `chatterbox`
-
-**Step 3b: Add Image Entries**
-
-Add image entries at the end of the file, following the pattern of similar backends such as `diffusers` or `chatterbox`. Include both `latest` (production) and `master` (development) tags.
-
-### 4. Update the Makefile
-
-The Makefile needs to be updated in several places to support building and testing the new backend:
-
-**Step 4a: Add to `.NOTPARALLEL`**
-
-Add `backends/<backend-name>` to the `.NOTPARALLEL` line (around line 2) to prevent parallel execution conflicts:
-
-```makefile
-.NOTPARALLEL: ... backends/<backend-name>
-```
-
-**Step 4b: Add to `prepare-test-extra`**
-
-Add the backend to the `prepare-test-extra` target (around line 312) to prepare it for testing:
-
-```makefile
-prepare-test-extra: protogen-python
-	...
-	$(MAKE) -C backend/python/<backend-name>
-```
-
-**Step 4c: Add to `test-extra`**
-
-Add the backend to the `test-extra` target (around line 319) to run its tests:
-
-```makefile
-test-extra: prepare-test-extra
-	...
-	$(MAKE) -C backend/python/<backend-name> test
-```
-
-**Step 4d: Add Backend Definition**
-
-Add a backend definition variable in the backend definitions section (around line 428-457). The format depends on the backend type:
-
-**For Python backends with root context** (like `faster-whisper`, `coqui`):
-```makefile
-BACKEND_<BACKEND_NAME> = <backend-name>|python|.|false|true
-```
-
-**For Python backends with `./backend` context** (like `chatterbox`, `moonshine`):
-```makefile
-BACKEND_<BACKEND_NAME> = <backend-name>|python|./backend|false|true
-```
-
-**For Go backends**:
-```makefile
-BACKEND_<BACKEND_NAME> = <backend-name>|golang|.|false|true
-```
-
-**Step 4e: Generate Docker Build Target**
-
-Add an eval call to generate the docker-build target (around line 480-501):
-
-```makefile
-$(eval $(call generate-docker-build-target,$(BACKEND_<BACKEND_NAME>)))
-```
-
-**Step 4f: Add to `docker-build-backends`**
-
-Add `docker-build-<backend-name>` to the `docker-build-backends` target (around line 507):
-
-```makefile
-docker-build-backends: ... docker-build-<backend-name>
-```
-
-**Determining the Context:**
-
-- If the backend is in `backend/python/<backend-name>/` and uses `./backend` as context in the workflow file, use `./backend` context
-- If the backend is in `backend/python/<backend-name>/` but uses `.` as context in the workflow file, use `.` context
-- Check similar backends to determine the correct context
-
-### 5. Verification Checklist
-
-After adding a new backend, verify:
-
-- [ ] Backend directory structure is complete with all necessary files
-- [ ] Build configurations added to `.github/workflows/backend.yml` for all desired platforms
-- [ ] Meta definition added to `backend/index.yaml` in the `## metas` section
-- [ ] Image entries added to `backend/index.yaml` for all build variants (latest + development)
-- [ ] Tag suffixes match between workflow file and index.yaml
-- [ ] Makefile updated with all 6 required changes (`.NOTPARALLEL`, `prepare-test-extra`, `test-extra`, backend definition, docker-build target eval, `docker-build-backends`)
-- [ ] No YAML syntax errors (check with linter)
-- [ ] No Makefile syntax errors (check with linter)
-- [ ] Follows the same pattern as similar backends (e.g., if it's a transcription backend, follow `faster-whisper` pattern)
-
-### 6. Example: Adding a Python Backend
-
-For reference, when `moonshine` was added:
-- **Files created**: `backend/python/moonshine/{backend.py, Makefile, install.sh, protogen.sh, requirements.txt, run.sh, test.py, test.sh}`
-- **Workflow entries**: 3 build configurations (CPU, CUDA 12, CUDA 13)
-- **Index entries**: 1 meta definition + 6 image entries (cpu, cuda12, cuda13 × latest/development)
-- **Makefile updates**: 
-  - Added to `.NOTPARALLEL` line
-  - Added to `prepare-test-extra` and `test-extra` targets
-  - Added `BACKEND_MOONSHINE = moonshine|python|./backend|false|true`
-  - Added eval for docker-build target generation
-  - Added `docker-build-moonshine` to `docker-build-backends`
-
-# Coding style
-
-- The project has the following .editorconfig
-
-```
-root = true
-
-[*]
-indent_style = space
-indent_size = 2
-end_of_line = lf
-charset = utf-8
-trim_trailing_whitespace = true
-insert_final_newline = true
-
-[*.go]
-indent_style = tab
-
-[Makefile]
-indent_style = tab
-
-[*.proto]
-indent_size = 2
-
-[*.py]
-indent_size = 4
-
-[*.js]
-indent_size = 2
-
-[*.yaml]
-indent_size = 2
-
-[*.md]
-trim_trailing_whitespace = false
-```
-
-- Use comments sparingly to explain why code does something, not what it does. Comments are there to add context that would be difficult to deduce from reading the code.
-- Prefer modern Go e.g. use `any` not `interface{}`
-
-# Logging
-
-Use `github.com/mudler/xlog` for logging which has the same API as slog.
-
-# llama.cpp Backend
-
-The llama.cpp backend (`backend/cpp/llama-cpp/grpc-server.cpp`) is a gRPC adaptation of the upstream HTTP server (`llama.cpp/tools/server/server.cpp`). It uses the same underlying server infrastructure from `llama.cpp/tools/server/server-context.cpp`.
-
-## Building and Testing
-
-- Test llama.cpp backend compilation: `make backends/llama-cpp`
-- The backend is built as part of the main build process
-- Check `backend/cpp/llama-cpp/Makefile` for build configuration
-
-## Architecture
-
-- **grpc-server.cpp**: gRPC server implementation, adapts HTTP server patterns to gRPC
-- Uses shared server infrastructure: `server-context.cpp`, `server-task.cpp`, `server-queue.cpp`, `server-common.cpp`
-- The gRPC server mirrors the HTTP server's functionality but uses gRPC instead of HTTP
-
-## Common Issues When Updating llama.cpp
-
-When fixing compilation errors after upstream changes:
-1. Check how `server.cpp` (HTTP server) handles the same change
-2. Look for new public APIs or getter methods
-3. Store copies of needed data instead of accessing private members
-4. Update function calls to match new signatures
-5. Test with `make backends/llama-cpp`
-
-## Key Differences from HTTP Server
-
-- gRPC uses `BackendServiceImpl` class with gRPC service methods
-- HTTP server uses `server_routes` with HTTP handlers
-- Both use the same `server_context` and task queue infrastructure
-- gRPC methods: `LoadModel`, `Predict`, `PredictStream`, `Embedding`, `Rerank`, `TokenizeString`, `GetMetrics`, `Health`
-
-## Tool Call Parsing Maintenance
-
-When working on JSON/XML tool call parsing functionality, always check llama.cpp for reference implementation and updates:
-
-### Checking for XML Parsing Changes
-
-1. **Review XML Format Definitions**: Check `llama.cpp/common/chat-parser-xml-toolcall.h` for `xml_tool_call_format` struct changes
-2. **Review Parsing Logic**: Check `llama.cpp/common/chat-parser-xml-toolcall.cpp` for parsing algorithm updates
-3. **Review Format Presets**: Check `llama.cpp/common/chat-parser.cpp` for new XML format presets (search for `xml_tool_call_format form`)
-4. **Review Model Lists**: Check `llama.cpp/common/chat.h` for `COMMON_CHAT_FORMAT_*` enum values that use XML parsing:
-   - `COMMON_CHAT_FORMAT_GLM_4_5`
-   - `COMMON_CHAT_FORMAT_MINIMAX_M2`
-   - `COMMON_CHAT_FORMAT_KIMI_K2`
-   - `COMMON_CHAT_FORMAT_QWEN3_CODER_XML`
-   - `COMMON_CHAT_FORMAT_APRIEL_1_5`
-   - `COMMON_CHAT_FORMAT_XIAOMI_MIMO`
-   - Any new formats added
-
-### Model Configuration Options
-
-Always check `llama.cpp` for new model configuration options that should be supported in LocalAI:
-
-1. **Check Server Context**: Review `llama.cpp/tools/server/server-context.cpp` for new parameters
-2. **Check Chat Params**: Review `llama.cpp/common/chat.h` for `common_chat_params` struct changes
-3. **Check Server Options**: Review `llama.cpp/tools/server/server.cpp` for command-line argument changes
-4. **Examples of options to check**:
-   - `ctx_shift` - Context shifting support
-   - `parallel_tool_calls` - Parallel tool calling
-   - `reasoning_format` - Reasoning format options
-   - Any new flags or parameters
-
-### Implementation Guidelines
-
-1. **Feature Parity**: Always aim for feature parity with llama.cpp's implementation
-2. **Test Coverage**: Add tests for new features matching llama.cpp's behavior
-3. **Documentation**: Update relevant documentation when adding new formats or options
-4. **Backward Compatibility**: Ensure changes don't break existing functionality
-
-### Files to Monitor
-
-- `llama.cpp/common/chat-parser-xml-toolcall.h` - Format definitions
-- `llama.cpp/common/chat-parser-xml-toolcall.cpp` - Parsing logic
-- `llama.cpp/common/chat-parser.cpp` - Format presets and model-specific handlers
-- `llama.cpp/common/chat.h` - Format enums and parameter structures
-- `llama.cpp/tools/server/server-context.cpp` - Server configuration options
-
-# Documentation
-
-The project documentation is located in `docs/content`. When adding new features or changing existing functionality, it is crucial to update the documentation to reflect these changes. This helps users understand how to use the new capabilities and ensures the documentation stays relevant.
-
-- **Feature Documentation**: If you add a new feature (like a new backend or API endpoint), create a new markdown file in `docs/content/features/` explaining what it is, how to configure it, and how to use it.
-- **Configuration**: If you modify configuration options, update the relevant sections in `docs/content/`.
-- **Examples**: providing concrete examples (like YAML configuration blocks) is highly encouraged to help users get started quickly.

CONTRIBUTING.md

@@ -30,7 +30,6 @@ Thank you for your interest in contributing to LocalAI! We appreciate your time
 3. Install the required dependencies ( see https://localai.io/basics/build/#build-localai-locally )
 4. Build LocalAI: `make build`
 5. Run LocalAI: `./local-ai`
-6. To Build and live reload: `make build-dev`
 
 ## Contributing
 
@@ -77,21 +76,7 @@ LOCALAI_IMAGE_TAG=test LOCALAI_IMAGE=local-ai-aio make run-e2e-aio
 ## Documentation
 
 We are welcome the contribution of the documents, please open new PR or create a new issue. The documentation is available under `docs/` https://github.com/mudler/LocalAI/tree/master/docs
-
-### Gallery YAML Schema
-
-LocalAI provides a JSON Schema for gallery model YAML files at:
-
-`core/schema/gallery-model.schema.json`
-
-This schema mirrors the internal gallery model configuration and can be used by editors (such as VS Code) to enable autocomplete, validation, and inline documentation when creating or modifying gallery files.
-
-To use it with the YAML language server, add the following comment at the top of a gallery YAML file:
-
-```yaml
-# yaml-language-server: $schema=../core/schema/gallery-model.schema.json
-```
-
+ 
 ## Community and Communication
 
 - You can reach out via the Github issue tracker.

Dockerfile

@@ -1,7 +1,6 @@
-ARG BASE_IMAGE=ubuntu:24.04
+ARG BASE_IMAGE=ubuntu:22.04
 ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
 ARG INTEL_BASE_IMAGE=${BASE_IMAGE}
-ARG UBUNTU_CODENAME=noble
 
 FROM ${BASE_IMAGE} AS requirements
 
@@ -10,7 +9,7 @@ ENV DEBIAN_FRONTEND=noninteractive
 RUN apt-get update && \
     apt-get install -y --no-install-recommends \
         ca-certificates curl wget espeak-ng libgomp1 \
-        ffmpeg libopenblas0 libopenblas-dev sox && \
+        ffmpeg libopenblas-base libopenblas-dev && \
     apt-get clean && \
     rm -rf /var/lib/apt/lists/*
 
@@ -24,7 +23,6 @@ ARG SKIP_DRIVERS=false
 ARG TARGETARCH
 ARG TARGETVARIANT
 ENV BUILD_TYPE=${BUILD_TYPE}
-ARG UBUNTU_VERSION=2404
 
 RUN mkdir -p /run/localai
 RUN echo "default" > /run/localai/capability
@@ -35,45 +33,11 @@ RUN <<EOT bash
         apt-get update && \
         apt-get install -y  --no-install-recommends \
             software-properties-common pciutils wget gpg-agent && \
-        apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
-            libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
-            libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
-            git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
-            ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
-            clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils mesa-vulkan-drivers
-        if [ "amd64" = "$TARGETARCH" ]; then
-            wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
-            tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            mkdir -p /opt/vulkan-sdk && \
-            mv 1.4.335.0 /opt/vulkan-sdk/ && \
-            cd /opt/vulkan-sdk/1.4.335.0 && \
-            ./vulkansdk --no-deps --maxjobs \
-                vulkan-loader \
-                vulkan-validationlayers \
-                vulkan-extensionlayer \
-                vulkan-tools \
-                shaderc && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
-            rm -rf /opt/vulkan-sdk
-        fi
-        if [ "arm64" = "$TARGETARCH" ]; then
-            mkdir vulkan && cd vulkan && \
-            curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
-            tar -xvf vulkan-sdk.tar.xz && \
-            rm vulkan-sdk.tar.xz && \
-            cd 1.4.335.0 && \
-            cp -rfv aarch64/bin/* /usr/bin/ && \
-            cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
-            cp -rfv aarch64/include/* /usr/include/ && \
-            cp -rfv aarch64/share/* /usr/share/ && \
-            cd ../.. && \
-            rm -rf vulkan
-        fi
-        ldconfig && \
+        wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
+        wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
+        apt-get update && \
+        apt-get install -y \
+            vulkan-sdk && \
         apt-get clean && \
         rm -rf /var/lib/apt/lists/* && \
         echo "vulkan" > /run/localai/capability
@@ -82,19 +46,15 @@ EOT
 
 # CuBLAS requirements
 RUN <<EOT bash
-    if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
+    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
         apt-get update && \
         apt-get install -y  --no-install-recommends \
             software-properties-common pciutils
         if [ "amd64" = "$TARGETARCH" ]; then
-            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
         fi
         if [ "arm64" = "$TARGETARCH" ]; then
-            if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
-            else
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
-            fi
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb
         fi
         dpkg -i cuda-keyring_1.1-1_all.deb && \
         rm -f cuda-keyring_1.1-1_all.deb && \
@@ -105,34 +65,16 @@ RUN <<EOT bash
             libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
             libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
             libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
-            apt-get install -y --no-install-recommends \
-            libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        fi
+            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && \
         apt-get clean && \
         rm -rf /var/lib/apt/lists/* && \
-        echo "nvidia-cuda-${CUDA_MAJOR_VERSION}" > /run/localai/capability
+        echo "nvidia" > /run/localai/capability
     fi
 EOT
 
 RUN <<EOT bash
     if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
-        echo "nvidia-l4t-cuda-${CUDA_MAJOR_VERSION}" > /run/localai/capability
-    fi
-EOT
-
-# https://github.com/NVIDIA/Isaac-GR00T/issues/343
-RUN <<EOT bash
-    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
-        wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
-        wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get install -y nvpl
+        echo "nvidia-l4t" > /run/localai/capability
     fi
 EOT
 
@@ -176,12 +118,13 @@ ENV PATH=/opt/rocm/bin:${PATH}
 # The requirements-core target is common to all images.  It should not be placed in requirements-core unless every single build will use it.
 FROM requirements-drivers AS build-requirements
 
-ARG GO_VERSION=1.25.4
-ARG CMAKE_VERSION=3.31.10
+ARG GO_VERSION=1.22.6
+ARG CMAKE_VERSION=3.26.4
 ARG CMAKE_FROM_SOURCE=false
 ARG TARGETARCH
 ARG TARGETVARIANT
 
+
 RUN apt-get update && \
     apt-get install -y --no-install-recommends \
         build-essential \
@@ -218,6 +161,14 @@ RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2 && \
 COPY --chmod=644 custom-ca-certs/* /usr/local/share/ca-certificates/
 RUN update-ca-certificates
 
+
+# OpenBLAS requirements and stable diffusion
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+        libopenblas-dev && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
 RUN test -n "$TARGETARCH" \
     || (echo 'warn: missing $TARGETARCH, either set this `ARG` manually, or run using `docker buildkit`')
 
@@ -238,10 +189,9 @@ WORKDIR /build
 # https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/APT-Repository-not-working-signatures-invalid/m-p/1599436/highlight/true#M36143
 # This is a temporary workaround until Intel fixes their repository
 FROM ${INTEL_BASE_IMAGE} AS intel
-ARG UBUNTU_CODENAME=noble
 RUN wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | \
 gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
-RUN echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu ${UBUNTU_CODENAME}/lts/2350 unified" > /etc/apt/sources.list.d/intel-graphics.list
+RUN echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy/lts/2350 unified" > /etc/apt/sources.list.d/intel-graphics.list
 RUN apt-get update && \
     apt-get install -y --no-install-recommends \
         intel-oneapi-runtime-libs && \
@@ -372,6 +322,6 @@ 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" ]

Dockerfile.aio

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

Makefile

@@ -1,20 +1,12 @@
-# Disable parallel execution for backend builds
-.NOTPARALLEL: backends/diffusers backends/llama-cpp backends/piper backends/stablediffusion-ggml backends/whisper backends/faster-whisper backends/silero-vad backends/local-store backends/huggingface backends/rfdetr backends/kitten-tts backends/kokoro backends/chatterbox backends/llama-cpp-darwin backends/neutts build-darwin-python-backend build-darwin-go-backend backends/mlx backends/diffuser-darwin backends/mlx-vlm backends/mlx-audio backends/stablediffusion-ggml-darwin backends/vllm backends/vllm-omni backends/moonshine backends/pocket-tts backends/qwen-tts backends/qwen-asr backends/voxcpm backends/whisperx
-
 GOCMD=go
 GOTEST=$(GOCMD) test
 GOVET=$(GOCMD) vet
 BINARY_NAME=local-ai
 LAUNCHER_BINARY_NAME=local-ai-launcher
 
-UBUNTU_VERSION?=2404
-UBUNTU_CODENAME?=noble
-
 GORELEASER?=
 
 export BUILD_TYPE?=
-export CUDA_MAJOR_VERSION?=13
-export CUDA_MINOR_VERSION?=0
 
 GO_TAGS?=
 BUILD_ID?=
@@ -111,10 +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
 
@@ -160,17 +148,7 @@ test: test-models/testmodel.ggml protogen-go
 ########################################################
 
 docker-build-aio:
-	docker build \
-		--build-arg MAKEFLAGS="--jobs=5 --output-sync=target" \
-		--build-arg BASE_IMAGE=$(BASE_IMAGE) \
-		--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
-		--build-arg BUILD_TYPE=$(BUILD_TYPE) \
-		--build-arg CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) \
-		--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
-		--build-arg UBUNTU_VERSION=$(UBUNTU_VERSION) \
-		--build-arg UBUNTU_CODENAME=$(UBUNTU_CODENAME) \
-		--build-arg GO_TAGS="$(GO_TAGS)" \
-		-t local-ai:tests -f Dockerfile .
+	docker build --build-arg MAKEFLAGS="--jobs=5 --output-sync=target" -t local-ai:tests -f Dockerfile .
 	BASE_IMAGE=local-ai:tests DOCKER_AIO_IMAGE=local-ai-aio:test $(MAKE) docker-aio
 
 e2e-aio:
@@ -189,29 +167,20 @@ run-e2e-aio: protogen-go
 ########################################################
 
 prepare-e2e:
-	docker build \
-		--build-arg IMAGE_TYPE=core \
-		--build-arg BUILD_TYPE=$(BUILD_TYPE) \
-		--build-arg BASE_IMAGE=$(BASE_IMAGE) \
-		--build-arg CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) \
-		--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
-		--build-arg UBUNTU_VERSION=$(UBUNTU_VERSION) \
-		--build-arg UBUNTU_CODENAME=$(UBUNTU_CODENAME) \
-		--build-arg GO_TAGS="$(GO_TAGS)" \
-		--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
-		-t localai-tests .
+	mkdir -p $(TEST_DIR)
+	cp -rfv $(abspath ./tests/e2e-fixtures)/gpu.yaml $(TEST_DIR)/gpu.yaml
+	test -e $(TEST_DIR)/ggllm-test-model.bin || wget -q https://huggingface.co/TheBloke/CodeLlama-7B-Instruct-GGUF/resolve/main/codellama-7b-instruct.Q2_K.gguf -O $(TEST_DIR)/ggllm-test-model.bin
+	docker build --build-arg IMAGE_TYPE=core --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg CUDA_MAJOR_VERSION=12 --build-arg CUDA_MINOR_VERSION=0 -t localai-tests .
 
 run-e2e-image:
-	docker run -p 5390:8080 -e MODELS_PATH=/models -e THREADS=1 -e DEBUG=true -d --rm -v $(TEST_DIR):/models --name e2e-tests-$(RANDOM) localai-tests
+	ls -liah $(abspath ./tests/e2e-fixtures)
+	docker run -p 5390:8080 -e MODELS_PATH=/models -e THREADS=1 -e DEBUG=true -d --rm -v $(TEST_DIR):/models --gpus all --name e2e-tests-$(RANDOM) localai-tests
 
-test-e2e: build-mock-backend prepare-e2e run-e2e-image
+test-e2e:
 	@echo 'Running e2e tests'
 	BUILD_TYPE=$(BUILD_TYPE) \
-	LOCALAI_API=http://$(E2E_BRIDGE_IP):5390 \
+	LOCALAI_API=http://$(E2E_BRIDGE_IP):5390/v1 \
 	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts $(TEST_FLAKES) -v -r ./tests/e2e
-	$(MAKE) clean-mock-backend
-	$(MAKE) teardown-e2e
-	docker rmi localai-tests
 
 teardown-e2e:
 	rm -rf $(TEST_DIR) || true
@@ -292,7 +261,7 @@ protoc:
 	  echo "Unsupported OS: $$OS_NAME"; exit 1; \
 	fi; \
 	URL=https://github.com/protocolbuffers/protobuf/releases/download/v31.1/$$FILE; \
-	curl -L $$URL -o protoc.zip && \
+	curl -L -s $$URL -o protoc.zip && \
 	unzip -j -d $(CURDIR) protoc.zip bin/protoc && rm protoc.zip
 
 .PHONY: protogen-go
@@ -311,33 +280,17 @@ prepare-test-extra: protogen-python
 	$(MAKE) -C backend/python/diffusers
 	$(MAKE) -C backend/python/chatterbox
 	$(MAKE) -C backend/python/vllm
-	$(MAKE) -C backend/python/vllm-omni
-	$(MAKE) -C backend/python/vibevoice
-	$(MAKE) -C backend/python/moonshine
-	$(MAKE) -C backend/python/pocket-tts
-	$(MAKE) -C backend/python/qwen-tts
-	$(MAKE) -C backend/python/qwen-asr
-	$(MAKE) -C backend/python/voxcpm
-	$(MAKE) -C backend/python/whisperx
 
 test-extra: prepare-test-extra
 	$(MAKE) -C backend/python/transformers test
 	$(MAKE) -C backend/python/diffusers test
 	$(MAKE) -C backend/python/chatterbox test
 	$(MAKE) -C backend/python/vllm test
-	$(MAKE) -C backend/python/vllm-omni test
-	$(MAKE) -C backend/python/vibevoice test
-	$(MAKE) -C backend/python/moonshine test
-	$(MAKE) -C backend/python/pocket-tts test
-	$(MAKE) -C backend/python/qwen-tts test
-	$(MAKE) -C backend/python/qwen-asr test
-	$(MAKE) -C backend/python/voxcpm test
-	$(MAKE) -C backend/python/whisperx test
 
 DOCKER_IMAGE?=local-ai
 DOCKER_AIO_IMAGE?=local-ai-aio
 IMAGE_TYPE?=core
-BASE_IMAGE?=ubuntu:24.04
+BASE_IMAGE?=ubuntu:22.04
 
 docker:
 	docker build \
@@ -346,34 +299,24 @@ docker:
 		--build-arg GO_TAGS="$(GO_TAGS)" \
 		--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
 		--build-arg BUILD_TYPE=$(BUILD_TYPE) \
-		--build-arg CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) \
-		--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
-		--build-arg UBUNTU_VERSION=$(UBUNTU_VERSION) \
-		--build-arg UBUNTU_CODENAME=$(UBUNTU_CODENAME) \
 		-t $(DOCKER_IMAGE) .
 
-docker-cuda12:
+docker-cuda11:
 	docker build \
-		--build-arg CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION} \
-		--build-arg CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION} \
+		--build-arg CUDA_MAJOR_VERSION=11 \
+		--build-arg CUDA_MINOR_VERSION=8 \
 		--build-arg BASE_IMAGE=$(BASE_IMAGE) \
 		--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
 		--build-arg GO_TAGS="$(GO_TAGS)" \
 		--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
 		--build-arg BUILD_TYPE=$(BUILD_TYPE) \
-		--build-arg UBUNTU_VERSION=$(UBUNTU_VERSION) \
-		--build-arg UBUNTU_CODENAME=$(UBUNTU_CODENAME) \
-		-t $(DOCKER_IMAGE)-cuda-12 .
+		-t $(DOCKER_IMAGE)-cuda-11 .
 
 docker-aio:
 	@echo "Building AIO image with base $(BASE_IMAGE) as $(DOCKER_AIO_IMAGE)"
 	docker build \
 		--build-arg BASE_IMAGE=$(BASE_IMAGE) \
 		--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
-		--build-arg CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) \
-		--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
-		--build-arg UBUNTU_VERSION=$(UBUNTU_VERSION) \
-		--build-arg UBUNTU_CODENAME=$(UBUNTU_CODENAME) \
 		-t $(DOCKER_AIO_IMAGE) -f Dockerfile.aio .
 
 docker-aio-all:
@@ -382,27 +325,53 @@ docker-aio-all:
 
 docker-image-intel:
 	docker build \
-		--build-arg BASE_IMAGE=intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04 \
+		--build-arg BASE_IMAGE=quay.io/go-skynet/intel-oneapi-base:latest \
 		--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
 		--build-arg GO_TAGS="$(GO_TAGS)" \
 		--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
-		--build-arg BUILD_TYPE=intel \
-		--build-arg CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) \
-		--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
-		--build-arg UBUNTU_VERSION=$(UBUNTU_VERSION) \
-		--build-arg UBUNTU_CODENAME=$(UBUNTU_CODENAME) \
-		-t $(DOCKER_IMAGE) .
+		--build-arg BUILD_TYPE=intel -t $(DOCKER_IMAGE) .
 
 ########################################################
 ## Backends
 ########################################################
 
-# Pattern rule for standard backends (docker-based)
-# This matches all backends that use docker-build-* and docker-save-*
-backends/%: docker-build-% docker-save-% build
-	./local-ai backends install "ocifile://$(abspath ./backend-images/$*.tar)"
 
-# Darwin-specific backends (keep as explicit targets since they have special build logic)
+backends/diffusers: docker-build-diffusers docker-save-diffusers build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/diffusers.tar)"
+
+backends/llama-cpp: docker-build-llama-cpp docker-save-llama-cpp build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/llama-cpp.tar)"
+
+backends/piper: docker-build-piper docker-save-piper build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/piper.tar)"
+
+backends/stablediffusion-ggml: docker-build-stablediffusion-ggml docker-save-stablediffusion-ggml build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/stablediffusion-ggml.tar)"
+
+backends/whisper: docker-build-whisper docker-save-whisper build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/whisper.tar)"
+
+backends/silero-vad: docker-build-silero-vad docker-save-silero-vad build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/silero-vad.tar)"
+
+backends/local-store: docker-build-local-store docker-save-local-store build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/local-store.tar)"
+
+backends/huggingface: docker-build-huggingface docker-save-huggingface build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/huggingface.tar)"
+
+backends/rfdetr: docker-build-rfdetr docker-save-rfdetr build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/rfdetr.tar)"
+
+backends/kitten-tts: docker-build-kitten-tts docker-save-kitten-tts build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/kitten-tts.tar)"
+
+backends/kokoro: docker-build-kokoro docker-save-kokoro build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/kokoro.tar)"
+
+backends/chatterbox: docker-build-chatterbox docker-save-chatterbox build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/chatterbox.tar)"
+
 backends/llama-cpp-darwin: build
 	bash ./scripts/build/llama-cpp-darwin.sh
 	./local-ai backends install "ocifile://$(abspath ./backend-images/llama-cpp.tar)"
@@ -436,102 +405,103 @@ backends/stablediffusion-ggml-darwin:
 backend-images:
 	mkdir -p backend-images
 
-# Backend metadata: BACKEND_NAME | DOCKERFILE_TYPE | BUILD_CONTEXT | PROGRESS_FLAG | NEEDS_BACKEND_ARG
-# llama-cpp is special - uses llama-cpp Dockerfile and doesn't need BACKEND arg
-BACKEND_LLAMA_CPP = llama-cpp|llama-cpp|.|false|false
+docker-build-llama-cpp:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:llama-cpp -f backend/Dockerfile.llama-cpp .
 
-# Golang backends
-BACKEND_PIPER = piper|golang|.|false|true
-BACKEND_LOCAL_STORE = local-store|golang|.|false|true
-BACKEND_HUGGINGFACE = huggingface|golang|.|false|true
-BACKEND_SILERO_VAD = silero-vad|golang|.|false|true
-BACKEND_STABLEDIFFUSION_GGML = stablediffusion-ggml|golang|.|--progress=plain|true
-BACKEND_WHISPER = whisper|golang|.|false|true
+docker-build-bark-cpp:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:bark-cpp -f backend/Dockerfile.golang --build-arg BACKEND=bark-cpp .
 
-# Python backends with root context
-BACKEND_RERANKERS = rerankers|python|.|false|true
-BACKEND_TRANSFORMERS = transformers|python|.|false|true
-BACKEND_FASTER_WHISPER = faster-whisper|python|.|false|true
-BACKEND_COQUI = coqui|python|.|false|true
-BACKEND_RFDETR = rfdetr|python|.|false|true
-BACKEND_KITTEN_TTS = kitten-tts|python|.|false|true
-BACKEND_NEUTTS = neutts|python|.|false|true
-BACKEND_KOKORO = kokoro|python|.|false|true
-BACKEND_VLLM = vllm|python|.|false|true
-BACKEND_VLLM_OMNI = vllm-omni|python|.|false|true
-BACKEND_DIFFUSERS = diffusers|python|.|--progress=plain|true
-BACKEND_CHATTERBOX = chatterbox|python|.|false|true
-BACKEND_VIBEVOICE = vibevoice|python|.|--progress=plain|true
-BACKEND_MOONSHINE = moonshine|python|.|false|true
-BACKEND_POCKET_TTS = pocket-tts|python|.|false|true
-BACKEND_QWEN_TTS = qwen-tts|python|.|false|true
-BACKEND_QWEN_ASR = qwen-asr|python|.|false|true
-BACKEND_VOXCPM = voxcpm|python|.|false|true
-BACKEND_WHISPERX = whisperx|python|.|false|true
+docker-build-piper:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:piper -f backend/Dockerfile.golang --build-arg BACKEND=piper .
 
-# Helper function to build docker image for a backend
-# Usage: $(call docker-build-backend,BACKEND_NAME,DOCKERFILE_TYPE,BUILD_CONTEXT,PROGRESS_FLAG,NEEDS_BACKEND_ARG)
-define docker-build-backend
-	docker build $(if $(filter-out false,$(4)),$(4)) \
-		--build-arg BUILD_TYPE=$(BUILD_TYPE) \
-		--build-arg BASE_IMAGE=$(BASE_IMAGE) \
-		--build-arg CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) \
-		--build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) \
-		--build-arg UBUNTU_VERSION=$(UBUNTU_VERSION) \
-		--build-arg UBUNTU_CODENAME=$(UBUNTU_CODENAME) \
-		$(if $(filter true,$(5)),--build-arg BACKEND=$(1)) \
-		-t local-ai-backend:$(1) -f backend/Dockerfile.$(2) $(3)
-endef
+docker-build-local-store:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:local-store -f backend/Dockerfile.golang --build-arg BACKEND=local-store .
 
-# Generate docker-build targets from backend definitions
-define generate-docker-build-target
-docker-build-$(word 1,$(subst |, ,$(1))):
-	$$(call docker-build-backend,$(word 1,$(subst |, ,$(1))),$(word 2,$(subst |, ,$(1))),$(word 3,$(subst |, ,$(1))),$(word 4,$(subst |, ,$(1))),$(word 5,$(subst |, ,$(1))))
-endef
+docker-build-huggingface:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:huggingface -f backend/Dockerfile.golang --build-arg BACKEND=huggingface .
 
-# Generate all docker-build targets
-$(eval $(call generate-docker-build-target,$(BACKEND_LLAMA_CPP)))
-$(eval $(call generate-docker-build-target,$(BACKEND_PIPER)))
-$(eval $(call generate-docker-build-target,$(BACKEND_LOCAL_STORE)))
-$(eval $(call generate-docker-build-target,$(BACKEND_HUGGINGFACE)))
-$(eval $(call generate-docker-build-target,$(BACKEND_SILERO_VAD)))
-$(eval $(call generate-docker-build-target,$(BACKEND_STABLEDIFFUSION_GGML)))
-$(eval $(call generate-docker-build-target,$(BACKEND_WHISPER)))
-$(eval $(call generate-docker-build-target,$(BACKEND_RERANKERS)))
-$(eval $(call generate-docker-build-target,$(BACKEND_TRANSFORMERS)))
-$(eval $(call generate-docker-build-target,$(BACKEND_FASTER_WHISPER)))
-$(eval $(call generate-docker-build-target,$(BACKEND_COQUI)))
-$(eval $(call generate-docker-build-target,$(BACKEND_RFDETR)))
-$(eval $(call generate-docker-build-target,$(BACKEND_KITTEN_TTS)))
-$(eval $(call generate-docker-build-target,$(BACKEND_NEUTTS)))
-$(eval $(call generate-docker-build-target,$(BACKEND_KOKORO)))
-$(eval $(call generate-docker-build-target,$(BACKEND_VLLM)))
-$(eval $(call generate-docker-build-target,$(BACKEND_VLLM_OMNI)))
-$(eval $(call generate-docker-build-target,$(BACKEND_DIFFUSERS)))
-$(eval $(call generate-docker-build-target,$(BACKEND_CHATTERBOX)))
-$(eval $(call generate-docker-build-target,$(BACKEND_VIBEVOICE)))
-$(eval $(call generate-docker-build-target,$(BACKEND_MOONSHINE)))
-$(eval $(call generate-docker-build-target,$(BACKEND_POCKET_TTS)))
-$(eval $(call generate-docker-build-target,$(BACKEND_QWEN_TTS)))
-$(eval $(call generate-docker-build-target,$(BACKEND_QWEN_ASR)))
-$(eval $(call generate-docker-build-target,$(BACKEND_VOXCPM)))
-$(eval $(call generate-docker-build-target,$(BACKEND_WHISPERX)))
+docker-build-rfdetr:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:rfdetr -f backend/Dockerfile.python --build-arg BACKEND=rfdetr ./backend
 
-# Pattern rule for docker-save targets
-docker-save-%: backend-images
-	docker save local-ai-backend:$* -o backend-images/$*.tar
+docker-build-kitten-tts:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:kitten-tts -f backend/Dockerfile.python --build-arg BACKEND=kitten-tts ./backend
 
-docker-build-backends: docker-build-llama-cpp docker-build-rerankers docker-build-vllm docker-build-vllm-omni docker-build-transformers docker-build-diffusers docker-build-kokoro docker-build-faster-whisper docker-build-coqui docker-build-chatterbox docker-build-vibevoice docker-build-moonshine docker-build-pocket-tts docker-build-qwen-tts docker-build-qwen-asr docker-build-voxcpm docker-build-whisperx
+docker-save-kitten-tts: backend-images
+	docker save local-ai-backend:kitten-tts -o backend-images/kitten-tts.tar
 
-########################################################
-### Mock Backend for E2E Tests
-########################################################
+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
 
-build-mock-backend: protogen-go
-	$(GOCMD) build -o tests/e2e/mock-backend/mock-backend ./tests/e2e/mock-backend
+docker-save-kokoro: backend-images
+	docker save local-ai-backend:kokoro -o backend-images/kokoro.tar
 
-clean-mock-backend:
-	rm -f tests/e2e/mock-backend/mock-backend
+docker-save-rfdetr: backend-images
+	docker save local-ai-backend:rfdetr -o backend-images/rfdetr.tar
+
+docker-save-huggingface: backend-images
+	docker save local-ai-backend:huggingface -o backend-images/huggingface.tar
+
+docker-save-local-store: backend-images
+	docker save local-ai-backend:local-store -o backend-images/local-store.tar
+
+docker-build-silero-vad:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:silero-vad -f backend/Dockerfile.golang --build-arg BACKEND=silero-vad .
+
+docker-save-silero-vad: backend-images
+	docker save local-ai-backend:silero-vad -o backend-images/silero-vad.tar
+
+docker-save-piper: backend-images
+	docker save local-ai-backend:piper -o backend-images/piper.tar
+
+docker-save-llama-cpp: backend-images
+	docker save local-ai-backend:llama-cpp -o backend-images/llama-cpp.tar
+
+docker-save-bark-cpp: backend-images
+	docker save local-ai-backend:bark-cpp -o backend-images/bark-cpp.tar
+
+docker-build-stablediffusion-ggml:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:stablediffusion-ggml -f backend/Dockerfile.golang --build-arg BACKEND=stablediffusion-ggml .
+
+docker-save-stablediffusion-ggml: backend-images
+	docker save local-ai-backend:stablediffusion-ggml -o backend-images/stablediffusion-ggml.tar
+
+docker-build-rerankers:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:rerankers -f backend/Dockerfile.python --build-arg BACKEND=rerankers .
+
+docker-build-vllm:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:vllm -f backend/Dockerfile.python --build-arg BACKEND=vllm .
+
+docker-build-transformers:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:transformers -f backend/Dockerfile.python --build-arg BACKEND=transformers .
+
+docker-build-diffusers:
+	docker build --progress=plain --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:diffusers -f backend/Dockerfile.python --build-arg BACKEND=diffusers ./backend
+
+docker-save-diffusers: backend-images
+	docker save local-ai-backend:diffusers -o backend-images/diffusers.tar
+
+docker-build-whisper:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:whisper -f backend/Dockerfile.golang --build-arg BACKEND=whisper  .
+
+docker-save-whisper: backend-images
+	docker save local-ai-backend:whisper -o backend-images/whisper.tar
+
+docker-build-faster-whisper:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:faster-whisper -f backend/Dockerfile.python --build-arg BACKEND=faster-whisper .
+
+docker-build-coqui:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:coqui -f backend/Dockerfile.python --build-arg BACKEND=coqui .
+
+docker-build-bark:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:bark -f backend/Dockerfile.python --build-arg BACKEND=bark .
+
+docker-build-chatterbox:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:chatterbox -f backend/Dockerfile.python --build-arg BACKEND=chatterbox ./backend
+
+docker-build-exllama2:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:exllama2 -f backend/Dockerfile.python --build-arg BACKEND=exllama2 .
+
+docker-build-backends: docker-build-llama-cpp docker-build-rerankers docker-build-vllm docker-build-transformers docker-build-diffusers docker-build-kokoro docker-build-faster-whisper docker-build-coqui docker-build-bark docker-build-chatterbox docker-build-exllama2
 
 ########################################################
 ### END Backends

README.md

@@ -33,7 +33,7 @@
 <img src="https://img.shields.io/badge/X-%23000000.svg?style=for-the-badge&logo=X&logoColor=white&label=LocalAI_API" alt="Follow LocalAI_API"/>
 </a>
 <a href="https://discord.gg/uJAeKSAGDy" target="blank">
-<img src="https://img.shields.io/badge/dynamic/json?color=blue&label=Discord&style=for-the-badge&query=approximate_member_count&url=https%3A%2F%2Fdiscordapp.com%2Fapi%2Finvites%2FuJAeKSAGDy%3Fwith_counts%3Dtrue&logo=discord" alt="Join LocalAI Discord Community"/>
+<img src="https://dcbadge.vercel.app/api/server/uJAeKSAGDy?style=flat-square&theme=default-inverted" alt="Join LocalAI Discord Community"/>
 </a>
 </p>
 
@@ -43,7 +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)
@@ -51,29 +51,37 @@
 **LocalAI** is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that's compatible with OpenAI (Elevenlabs, Anthropic... ) API specifications for local AI inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU. It is created and maintained by [Ettore Di Giacinto](https://github.com/mudler).
 
 
-## Local Stack Family
+## 📚🆕 Local Stack Family
 
-Liking LocalAI? LocalAI is part of an integrated suite of AI infrastructure tools, you might also like:
+🆕 LocalAI is now part of a comprehensive suite of AI tools designed to work together:
 
-- **[LocalAGI](https://github.com/mudler/LocalAGI)** - AI agent orchestration platform with OpenAI Responses API compatibility and advanced agentic capabilities
-- **[LocalRecall](https://github.com/mudler/LocalRecall)** - MCP/REST API knowledge base system providing persistent memory and storage for AI agents
-- 🆕 **[Cogito](https://github.com/mudler/cogito)** - Go library for building intelligent, co-operative agentic software and LLM-powered workflows, focusing on improving results for small, open source language models that scales to any LLM. Powers LocalAGI and LocalAI MCP/Agentic capabilities
-- 🆕 **[Wiz](https://github.com/mudler/wiz)** - Terminal-based AI agent accessible via Ctrl+Space keybinding. Portable, local-LLM friendly shell assistant with TUI/CLI modes, tool execution with approval, MCP protocol support, and multi-shell compatibility (zsh, bash, fish)
-- 🆕 **[SkillServer](https://github.com/mudler/skillserver)** - Simple, centralized skills database for AI agents via MCP. Manages skills as Markdown files with MCP server integration, web UI for editing, Git synchronization, and full-text search capabilities
+<table>
+  <tr>
+    <td width="50%" valign="top">
+      <a href="https://github.com/mudler/LocalAGI">
+        <img src="https://raw.githubusercontent.com/mudler/LocalAGI/refs/heads/main/webui/react-ui/public/logo_2.png" width="300" alt="LocalAGI Logo">
+      </a>
+    </td>
+    <td width="50%" valign="top">
+      <h3><a href="https://github.com/mudler/LocalAGI">LocalAGI</a></h3>
+      <p>A powerful Local AI agent management platform that serves as a drop-in replacement for OpenAI's Responses API, enhanced with advanced agentic capabilities.</p>
+    </td>
+  </tr>
+  <tr>
+    <td width="50%" valign="top">
+      <a href="https://github.com/mudler/LocalRecall">
+        <img src="https://raw.githubusercontent.com/mudler/LocalRecall/refs/heads/main/static/localrecall_horizontal.png" width="300" alt="LocalRecall Logo">
+      </a>
+    </td>
+    <td width="50%" valign="top">
+      <h3><a href="https://github.com/mudler/LocalRecall">LocalRecall</a></h3>
+      <p>A REST-ful API and knowledge base management system that provides persistent memory and storage capabilities for AI agents.</p>
+    </td>
+  </tr>
+</table>
 
+## Screenshots
 
-## Screenshots / Video
-
-### Youtube video
-
-<h1 align="center">
-  <br>
-  <a href="https://www.youtube.com/watch?v=PDqYhB9nNHA" target="_blank"> <img width="300" src="https://img.youtube.com/vi/PDqYhB9nNHA/0.jpg"> </a><br>
-<br>
-</h1>
-
-
-### Screenshots
 
 | Talk Interface | Generate Audio |
 | --- | --- |
@@ -93,8 +101,6 @@ Liking LocalAI? LocalAI is part of an integrated suite of AI infrastructure tool
 
 ## 💻 Quickstart
 
-> ⚠️ **Note:** The `install.sh` script is currently experiencing issues due to the heavy changes currently undergoing in LocalAI and may produce broken or misconfigured installations. Please use Docker installation (see below) or manual binary installation until [issue #8032](https://github.com/mudler/LocalAI/issues/8032) is resolved.
-
 Run the installer script:
 
 ```bash
@@ -102,7 +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:
 
@@ -110,70 +116,57 @@ 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:
 
-### Containers (Docker, podman, ...)
-
-> **💡 Docker Run vs Docker Start**
-> 
-> - `docker run` creates and starts a new container. If a container with the same name already exists, this command will fail.
-> - `docker start` starts an existing container that was previously created with `docker run`.
-> 
-> If you've already run LocalAI before and want to start it again, use: `docker start -i local-ai`
-
-#### CPU only image:
+### CPU only image:
 
 ```bash
 docker run -ti --name local-ai -p 8080:8080 localai/localai:latest
 ```
 
-#### NVIDIA GPU Images:
+### NVIDIA GPU Images:
 
 ```bash
-# CUDA 13.0
-docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-13
-
 # CUDA 12.0
 docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12
 
-# NVIDIA Jetson (L4T) ARM64
-# CUDA 12 (for Nvidia AGX Orin and similar platforms)
-docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nvidia-l4t-arm64
+# CUDA 11.7
+docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-11
 
-# CUDA 13 (for Nvidia DGX Spark)
-docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nvidia-l4t-arm64-cuda-13
+# NVIDIA Jetson (L4T) ARM64
+docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nvidia-l4t-arm64
 ```
 
-#### AMD GPU Images (ROCm):
+### AMD GPU Images (ROCm):
 
 ```bash
 docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri --group-add=video localai/localai:latest-gpu-hipblas
 ```
 
-#### Intel GPU Images (oneAPI):
+### Intel GPU Images (oneAPI):
 
 ```bash
 docker run -ti --name local-ai -p 8080:8080 --device=/dev/dri/card1 --device=/dev/dri/renderD128 localai/localai:latest-gpu-intel
 ```
 
-#### Vulkan GPU Images:
+### Vulkan GPU Images:
 
 ```bash
 docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-gpu-vulkan
 ```
 
-#### AIO Images (pre-downloaded models):
+### AIO Images (pre-downloaded models):
 
 ```bash
 # CPU version
 docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-cpu
 
-# NVIDIA CUDA 13 version
-docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-13
-
 # NVIDIA CUDA 12 version
 docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-12
 
+# NVIDIA CUDA 11 version
+docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-11
+
 # Intel GPU version
 docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-gpu-intel
 
@@ -200,14 +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
 
-- December 2025: [Dynamic Memory Resource reclaimer](https://github.com/mudler/LocalAI/pull/7583), [Automatic fitting of models to multiple GPUS(llama.cpp)](https://github.com/mudler/LocalAI/pull/7584), [Added Vibevoice backend](https://github.com/mudler/LocalAI/pull/7494)
-- November 2025: Major improvements to the UX. Among these: [Import models via URL](https://github.com/mudler/LocalAI/pull/7245) and [Multiple chats and history](https://github.com/mudler/LocalAI/pull/7325)
-- October 2025: 🔌 [Model Context Protocol (MCP)](https://localai.io/docs/features/mcp/) support added for agentic capabilities with external tools
-- September 2025: New Launcher application for MacOS and Linux, extended support to many backends for Mac and Nvidia L4T devices. Models: Added MLX-Audio, WAN 2.2. WebUI improvements and Python-based backends now ships portable python environments.
 - August 2025: MLX, MLX-VLM, Diffusers and llama.cpp are now supported on Mac M1/M2/M3+ chips ( with `development` suffix in the gallery ): https://github.com/mudler/LocalAI/pull/6049 https://github.com/mudler/LocalAI/pull/6119 https://github.com/mudler/LocalAI/pull/6121 https://github.com/mudler/LocalAI/pull/6060
 - July/August 2025: 🔍 [Object Detection](https://localai.io/features/object-detection/) added to the API featuring [rf-detr](https://github.com/roboflow/rf-detr)
 - July 2025: All backends migrated outside of the main binary. LocalAI is now more lightweight, small, and automatically downloads the required backend to run the model. [Read the release notes](https://github.com/mudler/LocalAI/releases/tag/v3.2.0)
@@ -239,7 +228,6 @@ Roadmap items: [List of issues](https://github.com/mudler/LocalAI/issues?q=is%3A
 - 🔈 [Audio to Text](https://localai.io/features/audio-to-text/) (Audio transcription with `whisper.cpp`)
 - 🎨 [Image generation](https://localai.io/features/image-generation)
 - 🔥 [OpenAI-alike tools API](https://localai.io/features/openai-functions/) 
-- ⚡ [Realtime API](https://localai.io/features/openai-realtime/) (Speech-to-speech) 
 - 🧠 [Embeddings generation for vector databases](https://localai.io/features/embeddings/)
 - ✍️ [Constrained grammars](https://localai.io/features/constrained_grammars/)
 - 🖼️ [Download Models directly from Huggingface ](https://localai.io/models/)
@@ -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!
 
@@ -258,39 +246,38 @@ LocalAI supports a comprehensive range of AI backends with multiple acceleration
 ### Text Generation & Language Models
 | Backend | Description | Acceleration Support |
 |---------|-------------|---------------------|
-| **llama.cpp** | LLM inference in C/C++ | CUDA 12/13, ROCm, Intel SYCL, Vulkan, Metal, CPU |
-| **vLLM** | Fast LLM inference with PagedAttention | CUDA 12/13, ROCm, Intel |
-| **transformers** | HuggingFace transformers framework | CUDA 12/13, ROCm, Intel, CPU |
+| **llama.cpp** | LLM inference in C/C++ | CUDA 11/12, ROCm, Intel SYCL, Vulkan, Metal, CPU |
+| **vLLM** | Fast LLM inference with PagedAttention | CUDA 12, ROCm, Intel |
+| **transformers** | HuggingFace transformers framework | CUDA 11/12, ROCm, Intel, CPU |
+| **exllama2** | GPTQ inference library | CUDA 12 |
 | **MLX** | Apple Silicon LLM inference | Metal (M1/M2/M3+) |
 | **MLX-VLM** | Apple Silicon Vision-Language Models | Metal (M1/M2/M3+) |
 
 ### Audio & Speech Processing
 | Backend | Description | Acceleration Support |
 |---------|-------------|---------------------|
-| **whisper.cpp** | OpenAI Whisper in C/C++ | CUDA 12/13, ROCm, Intel SYCL, Vulkan, CPU |
-| **faster-whisper** | Fast Whisper with CTranslate2 | CUDA 12/13, ROCm, Intel, CPU |
-| **coqui** | Advanced TTS with 1100+ languages | CUDA 12/13, ROCm, Intel, CPU |
-| **kokoro** | Lightweight TTS model | CUDA 12/13, ROCm, Intel, CPU |
-| **chatterbox** | Production-grade TTS | CUDA 12/13, CPU |
+| **whisper.cpp** | OpenAI Whisper in C/C++ | CUDA 12, ROCm, Intel SYCL, Vulkan, CPU |
+| **faster-whisper** | Fast Whisper with CTranslate2 | CUDA 12, ROCm, Intel, CPU |
+| **bark** | Text-to-audio generation | CUDA 12, ROCm, Intel |
+| **bark-cpp** | C++ implementation of Bark | CUDA, Metal, CPU |
+| **coqui** | Advanced TTS with 1100+ languages | CUDA 12, ROCm, Intel, CPU |
+| **kokoro** | Lightweight TTS model | CUDA 12, ROCm, Intel, CPU |
+| **chatterbox** | Production-grade TTS | CUDA 11/12, CPU |
 | **piper** | Fast neural TTS system | CPU |
 | **kitten-tts** | Kitten TTS models | CPU |
 | **silero-vad** | Voice Activity Detection | CPU |
-| **neutts** | Text-to-speech with voice cloning | CUDA 12/13, ROCm, CPU |
-| **vibevoice** | Real-time TTS with voice cloning | CUDA 12/13, ROCm, Intel, CPU |
-| **pocket-tts** | Lightweight CPU-based TTS | CUDA 12/13, ROCm, Intel, CPU |
-| **qwen-tts** | High-quality TTS with custom voice, voice design, and voice cloning | CUDA 12/13, ROCm, Intel, CPU |
 
 ### Image & Video Generation
 | Backend | Description | Acceleration Support |
 |---------|-------------|---------------------|
-| **stablediffusion.cpp** | Stable Diffusion in C/C++ | CUDA 12/13, Intel SYCL, Vulkan, CPU |
-| **diffusers** | HuggingFace diffusion models | CUDA 12/13, ROCm, Intel, Metal, CPU |
+| **stablediffusion.cpp** | Stable Diffusion in C/C++ | CUDA 12, Intel SYCL, Vulkan, CPU |
+| **diffusers** | HuggingFace diffusion models | CUDA 11/12, ROCm, Intel, Metal, CPU |
 
 ### Specialized AI Tasks
 | Backend | Description | Acceleration Support |
 |---------|-------------|---------------------|
-| **rfdetr** | Real-time object detection | CUDA 12/13, Intel, CPU |
-| **rerankers** | Document reranking API | CUDA 12/13, ROCm, Intel, CPU |
+| **rfdetr** | Real-time object detection | CUDA 12, Intel, CPU |
+| **rerankers** | Document reranking API | CUDA 11/12, ROCm, Intel, CPU |
 | **local-store** | Vector database | CPU |
 | **huggingface** | HuggingFace API integration | API-based |
 
@@ -298,14 +285,13 @@ LocalAI supports a comprehensive range of AI backends with multiple acceleration
 
 | Acceleration Type | Supported Backends | Hardware Support |
 |-------------------|-------------------|------------------|
+| **NVIDIA CUDA 11** | llama.cpp, whisper, stablediffusion, diffusers, rerankers, bark, chatterbox | Nvidia hardware |
 | **NVIDIA CUDA 12** | All CUDA-compatible backends | Nvidia hardware |
-| **NVIDIA CUDA 13** | All CUDA-compatible backends | Nvidia hardware |
-| **AMD ROCm** | llama.cpp, whisper, vllm, transformers, diffusers, rerankers, coqui, kokoro, neutts, vibevoice, pocket-tts, qwen-tts | AMD Graphics |
-| **Intel oneAPI** | llama.cpp, whisper, stablediffusion, vllm, transformers, diffusers, rfdetr, rerankers, coqui, kokoro, vibevoice, pocket-tts, qwen-tts | Intel Arc, Intel iGPUs |
-| **Apple Metal** | llama.cpp, whisper, diffusers, MLX, MLX-VLM | Apple M1/M2/M3+ |
+| **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 |
-| **NVIDIA Jetson (CUDA 12)** | llama.cpp, whisper, stablediffusion, diffusers, rfdetr | ARM64 embedded AI (AGX Orin, etc.) |
-| **NVIDIA Jetson (CUDA 13)** | llama.cpp, whisper, stablediffusion, diffusers, rfdetr | ARM64 embedded AI (DGX Spark) |
+| **NVIDIA Jetson** | llama.cpp, whisper, stablediffusion, diffusers, rfdetr | ARM64 embedded AI |
 | **CPU Optimized** | All backends | AVX/AVX2/AVX512, quantization support |
 
 ### 🔗 Community and integrations
@@ -318,16 +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
-
-OS Assistant:
-
-- https://github.com/mudler/Keygeist - Keygeist is an AI-powered keyboard operator that listens for key combinations and responds with AI-generated text typed directly into your Linux box.
-
 Model galleries
 - https://github.com/go-skynet/model-gallery
 
@@ -402,10 +378,6 @@ A huge thank you to our generous sponsors who support this project covering CI e
   </a>
 </p>
 
-### Individual sponsors
-
-A special thanks to individual sponsors that contributed to the project, a full list is in [Github](https://github.com/sponsors/mudler) and [buymeacoffee](https://buymeacoffee.com/mudler), a special shout out goes to [drikster80](https://github.com/drikster80) for being generous. Thank you everyone!
-
 ## 🌟 Star history
 
 [![LocalAI Star history Chart](https://api.star-history.com/svg?repos=go-skynet/LocalAI&type=Date)](https://star-history.com/#go-skynet/LocalAI&Date)

backend/Dockerfile.golang

@@ -1,4 +1,4 @@
-ARG BASE_IMAGE=ubuntu:24.04
+ARG BASE_IMAGE=ubuntu:22.04
 
 FROM ${BASE_IMAGE} AS builder
 ARG BACKEND=rerankers
@@ -12,15 +12,14 @@ ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
 ENV DEBIAN_FRONTEND=noninteractive
 ARG TARGETARCH
 ARG TARGETVARIANT
-ARG GO_VERSION=1.25.4
-ARG UBUNTU_VERSION=2404
+ARG GO_VERSION=1.22.6
 
 RUN apt-get update && \
     apt-get install -y --no-install-recommends \
         build-essential \
         git ccache \
         ca-certificates \
-        make cmake wget \
+        make cmake \
         curl unzip \
         libssl-dev && \
     apt-get clean && \
@@ -33,52 +32,17 @@ ENV PATH=/usr/local/cuda/bin:${PATH}
 # HipBLAS requirements
 ENV PATH=/opt/rocm/bin:${PATH}
 
-
 # Vulkan requirements
 RUN <<EOT bash
     if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
         apt-get update && \
         apt-get install -y  --no-install-recommends \
             software-properties-common pciutils wget gpg-agent && \
-        apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
-            libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
-            libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
-            git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
-            ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
-            clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
-        if [ "amd64" = "$TARGETARCH" ]; then
-            wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
-            tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            mkdir -p /opt/vulkan-sdk && \
-            mv 1.4.335.0 /opt/vulkan-sdk/ && \
-            cd /opt/vulkan-sdk/1.4.335.0 && \
-            ./vulkansdk --no-deps --maxjobs \
-                vulkan-loader \
-                vulkan-validationlayers \
-                vulkan-extensionlayer \
-                vulkan-tools \
-                shaderc && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
-            rm -rf /opt/vulkan-sdk
-        fi
-        if [ "arm64" = "$TARGETARCH" ]; then
-            mkdir vulkan && cd vulkan && \
-            curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
-            tar -xvf vulkan-sdk.tar.xz && \
-            rm vulkan-sdk.tar.xz && \
-            cd 1.4.335.0 && \
-            cp -rfv aarch64/bin/* /usr/bin/ && \
-            cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
-            cp -rfv aarch64/include/* /usr/include/ && \
-            cp -rfv aarch64/share/* /usr/share/ && \
-            cd ../.. && \
-            rm -rf vulkan
-        fi
-        ldconfig && \
+        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
@@ -86,19 +50,15 @@ EOT
 
 # CuBLAS requirements
 RUN <<EOT bash
-    if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
+    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
         apt-get update && \
         apt-get install -y  --no-install-recommends \
             software-properties-common pciutils
         if [ "amd64" = "$TARGETARCH" ]; then
-            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
         fi
         if [ "arm64" = "$TARGETARCH" ]; then
-            if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
-            else
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
-            fi
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb
         fi
         dpkg -i cuda-keyring_1.1-1_all.deb && \
         rm -f cuda-keyring_1.1-1_all.deb && \
@@ -109,31 +69,12 @@ RUN <<EOT bash
             libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
             libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
             libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
-            apt-get install -y --no-install-recommends \
-            libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        fi
+            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && \
         apt-get clean && \
         rm -rf /var/lib/apt/lists/*
     fi
 EOT
 
-
-# https://github.com/NVIDIA/Isaac-GR00T/issues/343
-RUN <<EOT bash
-    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
-        wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
-        wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get install -y nvpl
-    fi
-EOT
-
 # If we are building with clblas support, we need the libraries for the builds
 RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
         apt-get update && \
@@ -182,8 +123,6 @@ EOT
 
 COPY . /LocalAI
 
-RUN git config --global --add safe.directory /LocalAI
-
 RUN cd /LocalAI && make protogen-go && make -C /LocalAI/backend/go/${BACKEND} build
 
 FROM scratch

backend/Dockerfile.llama-cpp

@@ -1,4 +1,4 @@
-ARG BASE_IMAGE=ubuntu:24.04
+ARG BASE_IMAGE=ubuntu:22.04
 ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
 
 
@@ -10,8 +10,7 @@ FROM ${GRPC_BASE_IMAGE} AS grpc
 ARG GRPC_MAKEFLAGS="-j4 -Otarget"
 ARG GRPC_VERSION=v1.65.0
 ARG CMAKE_FROM_SOURCE=false
-# CUDA Toolkit 13.x compatibility: CMake 3.31.9+ fixes toolchain detection/arch table issues
-ARG CMAKE_VERSION=3.31.10
+ARG CMAKE_VERSION=3.26.4
 
 ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
 
@@ -21,13 +20,13 @@ RUN apt-get update && \
     apt-get install -y --no-install-recommends \
         ca-certificates \
         build-essential curl libssl-dev \
-        git wget && \
+        git && \
     apt-get clean && \
     rm -rf /var/lib/apt/lists/*
 
 # Install CMake (the version in 22.04 is too old)
 RUN <<EOT bash
-    if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
+    if [ "${CMAKE_FROM_SOURCE}}" = "true" ]; then
         curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
     else
         apt-get update && \
@@ -51,13 +50,6 @@ RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shall
     rm -rf /build
 
 FROM ${BASE_IMAGE} AS builder
-ARG CMAKE_FROM_SOURCE=false
-ARG CMAKE_VERSION=3.31.10
-# We can target specific CUDA ARCHITECTURES like --build-arg CUDA_DOCKER_ARCH='75;86;89;120'
-ARG CUDA_DOCKER_ARCH
-ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
-ARG CMAKE_ARGS
-ENV CMAKE_ARGS=${CMAKE_ARGS}
 ARG BACKEND=rerankers
 ARG BUILD_TYPE
 ENV BUILD_TYPE=${BUILD_TYPE}
@@ -69,8 +61,7 @@ ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
 ENV DEBIAN_FRONTEND=noninteractive
 ARG TARGETARCH
 ARG TARGETVARIANT
-ARG GO_VERSION=1.25.4
-ARG UBUNTU_VERSION=2404
+ARG GO_VERSION=1.22.6
 
 RUN apt-get update && \
     apt-get install -y --no-install-recommends \
@@ -78,9 +69,8 @@ RUN apt-get update && \
         ccache git \
         ca-certificates \
         make \
-        pkg-config libcurl4-openssl-dev \
         curl unzip \
-        libssl-dev wget && \
+        libssl-dev && \
     apt-get clean && \
     rm -rf /var/lib/apt/lists/*
 
@@ -90,52 +80,17 @@ ENV PATH=/usr/local/cuda/bin:${PATH}
 # HipBLAS requirements
 ENV PATH=/opt/rocm/bin:${PATH}
 
-
 # Vulkan requirements
 RUN <<EOT bash
     if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
         apt-get update && \
         apt-get install -y  --no-install-recommends \
             software-properties-common pciutils wget gpg-agent && \
-        apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
-            libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
-            libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
-            git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
-            ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
-            clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
-        if [ "amd64" = "$TARGETARCH" ]; then
-            wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
-            tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            mkdir -p /opt/vulkan-sdk && \
-            mv 1.4.335.0 /opt/vulkan-sdk/ && \
-            cd /opt/vulkan-sdk/1.4.335.0 && \
-            ./vulkansdk --no-deps --maxjobs \
-                vulkan-loader \
-                vulkan-validationlayers \
-                vulkan-extensionlayer \
-                vulkan-tools \
-                shaderc && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
-            rm -rf /opt/vulkan-sdk
-        fi
-        if [ "arm64" = "$TARGETARCH" ]; then
-            mkdir vulkan && cd vulkan && \
-            curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
-            tar -xvf vulkan-sdk.tar.xz && \
-            rm vulkan-sdk.tar.xz && \
-            cd 1.4.335.0 && \
-            cp -rfv aarch64/bin/* /usr/bin/ && \
-            cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
-            cp -rfv aarch64/include/* /usr/include/ && \
-            cp -rfv aarch64/share/* /usr/share/ && \
-            cd ../.. && \
-            rm -rf vulkan
-        fi
-        ldconfig && \
+        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
@@ -143,19 +98,15 @@ EOT
 
 # CuBLAS requirements
 RUN <<EOT bash
-    if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
+    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
         apt-get update && \
         apt-get install -y  --no-install-recommends \
             software-properties-common pciutils
         if [ "amd64" = "$TARGETARCH" ]; then
-            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
         fi
         if [ "arm64" = "$TARGETARCH" ]; then
-            if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
-            else
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
-            fi
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb
         fi
         dpkg -i cuda-keyring_1.1-1_all.deb && \
         rm -f cuda-keyring_1.1-1_all.deb && \
@@ -166,31 +117,12 @@ RUN <<EOT bash
             libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
             libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
             libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
-            apt-get install -y --no-install-recommends \
-            libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        fi
+            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && \
         apt-get clean && \
         rm -rf /var/lib/apt/lists/*
     fi
 EOT
 
-
-# https://github.com/NVIDIA/Isaac-GR00T/issues/343
-RUN <<EOT bash
-    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
-        wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
-        wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get install -y nvpl
-    fi
-EOT
-
 # If we are building with clblas support, we need the libraries for the builds
 RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
         apt-get update && \
@@ -232,7 +164,7 @@ EOT
 
 # Install CMake (the version in 22.04 is too old)
 RUN <<EOT bash
-    if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
+    if [ "${CMAKE_FROM_SOURCE}}" = "true" ]; then
         curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
     else
         apt-get update && \
@@ -248,35 +180,24 @@ COPY --from=grpc /opt/grpc /usr/local
 
 COPY . /LocalAI
 
-RUN <<'EOT' bash
-set -euxo pipefail
-
-if [[ -n "${CUDA_DOCKER_ARCH:-}" ]]; then
-  CUDA_ARCH_ESC="${CUDA_DOCKER_ARCH//;/\\;}"
-  export CMAKE_ARGS="${CMAKE_ARGS:-} -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCH_ESC}"
-  echo "CMAKE_ARGS(env) = ${CMAKE_ARGS}"
-  rm -rf /LocalAI/backend/cpp/llama-cpp-*-build
-fi
-
-if [ "${TARGETARCH}" = "arm64" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then
-  cd /LocalAI/backend/cpp/llama-cpp
-  make llama-cpp-fallback
-  make llama-cpp-grpc
-  make llama-cpp-rpc-server
-else
-  cd /LocalAI/backend/cpp/llama-cpp
-  make llama-cpp-avx
-  make llama-cpp-avx2
-  make llama-cpp-avx512
-  make llama-cpp-fallback
-  make llama-cpp-grpc
-  make llama-cpp-rpc-server
-fi
+## Otherwise just run the normal build
+RUN <<EOT bash
+if [ "${TARGETARCH}" = "arm64" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then \
+        cd /LocalAI/backend/cpp/llama-cpp && make llama-cpp-fallback && \
+        make llama-cpp-grpc && make llama-cpp-rpc-server; \
+    else \
+        cd /LocalAI/backend/cpp/llama-cpp && make llama-cpp-avx && \
+        make llama-cpp-avx2 && \
+        make llama-cpp-avx512 && \
+        make llama-cpp-fallback && \
+        make llama-cpp-grpc && \
+        make llama-cpp-rpc-server; \
+    fi  
 EOT
 
 
 # Copy libraries using a script to handle architecture differences
-RUN make -BC /LocalAI/backend/cpp/llama-cpp package
+RUN make -C /LocalAI/backend/cpp/llama-cpp package
 
 
 FROM scratch

backend/Dockerfile.python

@@ -1,4 +1,4 @@
-ARG BASE_IMAGE=ubuntu:24.04
+ARG BASE_IMAGE=ubuntu:22.04
 
 FROM ${BASE_IMAGE} AS builder
 ARG BACKEND=rerankers
@@ -12,7 +12,6 @@ ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
 ENV DEBIAN_FRONTEND=noninteractive
 ARG TARGETARCH
 ARG TARGETVARIANT
-ARG UBUNTU_VERSION=2404
 
 RUN apt-get update && \
     apt-get install -y --no-install-recommends \
@@ -22,24 +21,17 @@ RUN apt-get update && \
         espeak-ng \
         curl \
         libssl-dev \
-        git wget \
+        git \
         git-lfs \
         unzip clang \
         upx-ucl \
         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/*
-
-RUN <<EOT bash
-    if [ "${UBUNTU_VERSION}" = "2404" ]; then
-        pip install --break-system-packages --user --upgrade pip
-    else
-        pip install --upgrade pip
-    fi
-EOT
+    rm -rf /var/lib/apt/lists/* && \
+    pip install --upgrade pip
 
 
 # Cuda
@@ -54,45 +46,11 @@ RUN <<EOT bash
         apt-get update && \
         apt-get install -y  --no-install-recommends \
             software-properties-common pciutils wget gpg-agent && \
-        apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
-            libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
-            libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
-            git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
-            ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
-            clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
-        if [ "amd64" = "$TARGETARCH" ]; then
-            wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
-            tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
-            mkdir -p /opt/vulkan-sdk && \
-            mv 1.4.335.0 /opt/vulkan-sdk/ && \
-            cd /opt/vulkan-sdk/1.4.335.0 && \
-            ./vulkansdk --no-deps --maxjobs \
-                vulkan-loader \
-                vulkan-validationlayers \
-                vulkan-extensionlayer \
-                vulkan-tools \
-                shaderc && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
-            rm -rf /opt/vulkan-sdk
-        fi
-        if [ "arm64" = "$TARGETARCH" ]; then
-            mkdir vulkan && cd vulkan && \
-            curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
-            tar -xvf vulkan-sdk.tar.xz && \
-            rm vulkan-sdk.tar.xz && \
-            cd 1.4.335.0 && \
-            cp -rfv aarch64/bin/* /usr/bin/ && \
-            cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
-            cp -rfv aarch64/include/* /usr/include/ && \
-            cp -rfv aarch64/share/* /usr/share/ && \
-            cd ../.. && \
-            rm -rf vulkan
-        fi
-        ldconfig && \
+        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
@@ -100,19 +58,15 @@ EOT
 
 # CuBLAS requirements
 RUN <<EOT bash
-    if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
+    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
         apt-get update && \
         apt-get install -y  --no-install-recommends \
             software-properties-common pciutils
         if [ "amd64" = "$TARGETARCH" ]; then
-            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
         fi
         if [ "arm64" = "$TARGETARCH" ]; then
-            if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
-            else
-                curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
-            fi
+            curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb
         fi
         dpkg -i cuda-keyring_1.1-1_all.deb && \
         rm -f cuda-keyring_1.1-1_all.deb && \
@@ -123,31 +77,12 @@ RUN <<EOT bash
             libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
             libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
             libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
-            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
-            apt-get install -y --no-install-recommends \
-            libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
-        fi
+            libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && \
         apt-get clean && \
         rm -rf /var/lib/apt/lists/*
     fi
 EOT
 
-
-# https://github.com/NVIDIA/Isaac-GR00T/issues/343
-RUN <<EOT bash
-    if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
-        wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
-        cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
-        wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
-        cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
-        apt-get update && apt-get install -y nvpl
-    fi
-EOT
-
 # If we are building with clblas support, we need the libraries for the builds
 RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
         apt-get update && \
@@ -168,40 +103,21 @@ RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
         # to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
         ldconfig \
     ; fi
-
-RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
-    ln -s /opt/rocm-**/lib/llvm/lib/libomp.so /usr/lib/libomp.so \
-    ; fi
-
 # Install uv as a system package
 RUN curl -LsSf https://astral.sh/uv/install.sh | UV_INSTALL_DIR=/usr/bin sh
 ENV PATH="/root/.cargo/bin:${PATH}"
-# Increase timeout for uv installs behind slow networks
-ENV UV_HTTP_TIMEOUT=180
+
 RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
 
 # Install grpcio-tools (the version in 22.04 is too old)
-RUN <<EOT bash
-    if [ "${UBUNTU_VERSION}" = "2404" ]; then
-        pip install --break-system-packages --user grpcio-tools==1.71.0 grpcio==1.71.0
-    else
-        pip install grpcio-tools==1.71.0 grpcio==1.71.0
-    fi
-EOT
+RUN pip install --user grpcio-tools==1.71.0 grpcio==1.71.0
 
-
-COPY backend/python/${BACKEND} /${BACKEND}
-COPY backend/backend.proto /${BACKEND}/backend.proto
-COPY backend/python/common/ /${BACKEND}/common
-COPY scripts/build/package-gpu-libs.sh /package-gpu-libs.sh
+COPY python/${BACKEND} /${BACKEND}
+COPY backend.proto /${BACKEND}/backend.proto
+COPY python/common/ /${BACKEND}/common
 
 RUN cd /${BACKEND} && PORTABLE_PYTHON=true make
 
-# Package GPU libraries into the backend's lib directory
-RUN mkdir -p /${BACKEND}/lib && \
-    TARGET_LIB_DIR="/${BACKEND}/lib" BUILD_TYPE="${BUILD_TYPE}" CUDA_MAJOR_VERSION="${CUDA_MAJOR_VERSION}" \
-    bash /package-gpu-libs.sh "/${BACKEND}/lib"
-
 FROM scratch
 ARG BACKEND=rerankers
 COPY --from=builder /${BACKEND}/ /

backend/README.md

@@ -46,7 +46,7 @@ The backend system provides language-specific Dockerfiles that handle the build
 - **vllm**: High-performance LLM inference
 - **mlx**: Apple Silicon optimization
 - **diffusers**: Stable Diffusion models
-- **Audio**: coqui, faster-whisper, kitten-tts
+- **Audio**: bark, coqui, faster-whisper, kitten-tts
 - **Vision**: mlx-vlm, rfdetr
 - **Specialized**: rerankers, chatterbox, kokoro
 
@@ -55,6 +55,7 @@ The backend system provides language-specific Dockerfiles that handle the build
 - **stablediffusion-ggml**: Stable Diffusion in Go with GGML Cpp backend
 - **huggingface**: Hugging Face model integration
 - **piper**: Text-to-speech synthesis Golang with C bindings using rhaspy/piper
+- **bark-cpp**: Bark TTS models Golang with Cpp bindings
 - **local-store**: Vector storage backend
 
 #### C++ Backends (`cpp/`)
@@ -64,7 +65,7 @@ The backend system provides language-specific Dockerfiles that handle the build
 ## Hardware Acceleration Support
 
 ### CUDA (NVIDIA)
-- **Versions**: CUDA 12.x, 13.x
+- **Versions**: CUDA 11.x, 12.x
 - **Features**: cuBLAS, cuDNN, TensorRT optimization
 - **Targets**: x86_64, ARM64 (Jetson)
 
@@ -131,7 +132,8 @@ For ARM64/Mac builds, docker can't be used, and the makefile in the respective b
 ### Build Types
 
 - **`cpu`**: CPU-only optimization
-- **`cublas12`**, **`cublas13`**: CUDA 12.x, 13.x with cuBLAS
+- **`cublas11`**: CUDA 11.x with cuBLAS
+- **`cublas12`**: CUDA 12.x with cuBLAS
 - **`hipblas`**: ROCm with rocBLAS
 - **`intel`**: Intel oneAPI optimization
 - **`vulkan`**: Vulkan-based acceleration
@@ -208,4 +210,4 @@ When contributing to the backend system:
 2. **Add Tests**: Include comprehensive test coverage
 3. **Document**: Provide clear usage examples
 4. **Optimize**: Consider performance and resource usage
-5. **Validate**: Test across different hardware targets
+5. **Validate**: Test across different hardware targets

backend/backend.proto

@@ -17,7 +17,6 @@ service Backend {
   rpc GenerateVideo(GenerateVideoRequest) returns (Result) {}
   rpc AudioTranscription(TranscriptRequest) returns (TranscriptResult) {}
   rpc TTS(TTSRequest) returns (Result) {}
-  rpc TTSStream(TTSRequest) returns (stream Reply) {}
   rpc SoundGeneration(SoundGenerationRequest) returns (Result) {}
   rpc TokenizeString(PredictOptions) returns (TokenizationResponse) {}
   rpc Status(HealthMessage) returns (StatusResponse) {}
@@ -33,8 +32,6 @@ service Backend {
   rpc GetMetrics(MetricsRequest) returns (MetricsResponse);
 
   rpc VAD(VADRequest) returns (VADResponse) {}
-
-  rpc ModelMetadata(ModelOptions) returns (ModelMetadataResponse) {}
 }
 
 // Define the empty request
@@ -157,10 +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
@@ -171,7 +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 {
@@ -285,7 +277,6 @@ message TranscriptRequest {
   uint32 threads = 4;
   bool translate = 5;
   bool diarize = 6;
-  string prompt = 7;
 }
 
 message TranscriptResult {
@@ -299,12 +290,12 @@ message TranscriptSegment {
   int64 end = 3;
   string text = 4;
   repeated int32 tokens = 5;
-  string speaker = 6;
 }
 
 message GenerateImageRequest {
   int32 height = 1;
   int32 width = 2;
+  int32 mode = 3;
   int32 step = 4;
   int32 seed = 5;
   string positive_prompt = 6;
@@ -391,11 +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 {
@@ -414,8 +400,3 @@ message Detection {
 message DetectResponse {
   repeated Detection Detections = 1;
 }
-
-message ModelMetadataResponse {
-  bool supports_thinking = 1;
-  string rendered_template = 2;  // The rendered chat template with enable_thinking=true (empty if not applicable)
-}

backend/cpp/llama-cpp/CMakeLists.txt

@@ -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 ${CMAKE_SOURCE_DIR})
@@ -70,4 +70,4 @@ target_link_libraries(${TARGET} PRIVATE common llama mtmd ${CMAKE_THREAD_LIBS_IN
 target_compile_features(${TARGET} PRIVATE cxx_std_11)
 if(TARGET BUILD_INFO)
   add_dependencies(${TARGET} BUILD_INFO)
-endif()
+endif()

backend/cpp/llama-cpp/Makefile

@@ -1,5 +1,5 @@
 
-LLAMA_VERSION?=2634ed207a17db1a54bd8df0555bd8499a6ab691
+LLAMA_VERSION?=8ff206097c2bf3ca1c7aa95f9d6db779fc7bdd68
 LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
 
 CMAKE_ARGS?=
@@ -7,15 +7,14 @@ BUILD_TYPE?=
 NATIVE?=false
 ONEAPI_VARS?=/opt/intel/oneapi/setvars.sh
 TARGET?=--target grpc-server
-JOBS?=$(shell nproc 2>/dev/null || sysctl -n hw.ncpu 2>/dev/null || echo 1)
-ARCH?=$(shell uname -m)
+JOBS?=$(shell nproc)
 
 # Disable Shared libs as we are linking on static gRPC and we can't mix shared and static
 CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF -DLLAMA_CURL=OFF
 
 CURRENT_MAKEFILE_DIR := $(dir $(abspath $(lastword $(MAKEFILE_LIST))))
 ifeq ($(NATIVE),false)
-	CMAKE_ARGS+=-DGGML_NATIVE=OFF -DLLAMA_OPENSSL=OFF
+	CMAKE_ARGS+=-DGGML_NATIVE=OFF
 endif
 # If build type is cublas, then we set -DGGML_CUDA=ON to CMAKE_ARGS automatically
 ifeq ($(BUILD_TYPE),cublas)
@@ -107,21 +106,21 @@ llama-cpp-avx: llama.cpp
 	cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx-build
 	$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx-build purge
 	$(info ${GREEN}I llama-cpp build info:avx${RESET})
-	CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_BMI2=off" $(MAKE) VARIANT="llama-cpp-avx-build" build-llama-cpp-grpc-server
+	CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off" $(MAKE) VARIANT="llama-cpp-avx-build" build-llama-cpp-grpc-server
 	cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx-build/grpc-server llama-cpp-avx
 
 llama-cpp-fallback: llama.cpp
 	cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-fallback-build
 	$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-fallback-build purge
 	$(info ${GREEN}I llama-cpp build info:fallback${RESET})
-	CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_BMI2=off" $(MAKE) VARIANT="llama-cpp-fallback-build" build-llama-cpp-grpc-server
+	CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off" $(MAKE) VARIANT="llama-cpp-fallback-build" build-llama-cpp-grpc-server
 	cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-fallback-build/grpc-server llama-cpp-fallback
 
 llama-cpp-grpc: llama.cpp
 	cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build
 	$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build purge
 	$(info ${GREEN}I llama-cpp build info:grpc${RESET})
-	CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_RPC=ON -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_BMI2=off" TARGET="--target grpc-server --target rpc-server" $(MAKE) VARIANT="llama-cpp-grpc-build" build-llama-cpp-grpc-server
+	CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_RPC=ON -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off" TARGET="--target grpc-server --target rpc-server" $(MAKE) VARIANT="llama-cpp-grpc-build" build-llama-cpp-grpc-server
 	cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build/grpc-server llama-cpp-grpc
 
 llama-cpp-rpc-server: llama-cpp-grpc

backend/cpp/llama-cpp/package.sh

@@ -6,7 +6,6 @@
 set -e
 
 CURDIR=$(dirname "$(realpath $0)")
-REPO_ROOT="${CURDIR}/../../.."
 
 # Create lib directory
 mkdir -p $CURDIR/package/lib
@@ -38,15 +37,6 @@ else
     exit 1
 fi
 
-# Package GPU libraries based on BUILD_TYPE
-# The GPU library packaging script will detect BUILD_TYPE and copy appropriate GPU libraries
-GPU_LIB_SCRIPT="${REPO_ROOT}/scripts/build/package-gpu-libs.sh"
-if [ -f "$GPU_LIB_SCRIPT" ]; then
-    echo "Packaging GPU libraries for BUILD_TYPE=${BUILD_TYPE:-cpu}..."
-    source "$GPU_LIB_SCRIPT" "$CURDIR/package/lib"
-    package_gpu_libs
-fi
-
 echo "Packaging completed successfully" 
 ls -liah $CURDIR/package/
 ls -liah $CURDIR/package/lib/

backend/cpp/llama-cpp/patches/01-llava.patch

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

backend/cpp/llama-cpp/prepare.sh

@@ -1,24 +1,18 @@
 #!/bin/bash
 
 ## Patches
-
 ## Apply patches from the `patches` directory
-if [ -d "patches" ]; then
-    for patch in $(ls patches); do
-        echo "Applying patch $patch"
-        patch -d llama.cpp/ -p1 < patches/$patch
-    done 
-fi
+for patch in $(ls patches); do
+    echo "Applying patch $patch"
+    patch -d llama.cpp/ -p1 < patches/$patch
+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
@@ -29,3 +23,30 @@ else
 fi
 set -e
 
+# Now to keep maximum compatibility with the original server.cpp, we need to remove the index.html.gz.hpp and loading.html.hpp includes
+# and remove the main function
+# TODO: upstream this to the original server.cpp by extracting the upstream main function to a separate file
+awk '
+/int[ \t]+main[ \t]*\(/ {          # If the line starts the main function
+    in_main=1;                     # Set a flag
+    open_braces=0;                 # Track number of open braces
+}
+in_main {
+    open_braces += gsub(/\{/, "{"); # Count opening braces
+    open_braces -= gsub(/\}/, "}"); # Count closing braces
+    if (open_braces == 0) {         # If all braces are closed
+        in_main=0;                  # End skipping
+    }
+    next;                           # Skip lines inside main
+}
+!in_main                           # Print lines not inside main
+' "llama.cpp/tools/server/server.cpp" > llama.cpp/tools/grpc-server/server.cpp
+
+# remove index.html.gz.hpp and loading.html.hpp includes
+if [[ "$OSTYPE" == "darwin"* ]]; then
+    # macOS
+    sed -i '' '/#include "index\.html\.gz\.hpp"/d; /#include "loading\.html\.hpp"/d' llama.cpp/tools/grpc-server/server.cpp
+else
+    # Linux and others
+    sed -i '/#include "index\.html\.gz\.hpp"/d; /#include "loading\.html\.hpp"/d' llama.cpp/tools/grpc-server/server.cpp
+fi

backend/go/bark-cpp/Makefile

@@ -0,0 +1,51 @@
+INCLUDE_PATH := $(abspath ./)
+LIBRARY_PATH := $(abspath ./)
+
+AR?=ar
+
+CMAKE_ARGS?=-DGGML_NATIVE=OFF
+BUILD_TYPE?=
+GOCMD=go
+# keep standard at C11 and C++11
+CXXFLAGS = -I. -I$(INCLUDE_PATH)/sources/bark.cpp/examples -I$(INCLUDE_PATH)/sources/bark.cpp/encodec.cpp/ggml/include -I$(INCLUDE_PATH)/sources/bark.cpp/spm-headers -I$(INCLUDE_PATH)/sources/bark.cpp -O3 -DNDEBUG -std=c++17 -fPIC
+LDFLAGS  = -L$(LIBRARY_PATH) -L$(LIBRARY_PATH)/sources/bark.cpp/build/examples -lbark -lstdc++ -lm
+
+# bark.cpp
+BARKCPP_REPO?=https://github.com/PABannier/bark.cpp.git
+BARKCPP_VERSION?=5d5be84f089ab9ea53b7a793f088d3fbf7247495
+
+# warnings
+CXXFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function
+
+## bark.cpp
+sources/bark.cpp:
+	git clone --recursive $(BARKCPP_REPO) sources/bark.cpp && \
+	cd sources/bark.cpp && \
+	git checkout $(BARKCPP_VERSION) && \
+	git submodule update --init --recursive --depth 1 --single-branch
+
+sources/bark.cpp/build/libbark.a: sources/bark.cpp
+	cd sources/bark.cpp && \
+	mkdir -p build && \
+	cd build && \
+	cmake $(CMAKE_ARGS) .. && \
+	cmake --build . --config Release
+
+gobark.o:
+	$(CXX) $(CXXFLAGS) gobark.cpp -o gobark.o -c $(LDFLAGS)
+
+libbark.a: sources/bark.cpp/build/libbark.a gobark.o
+	cp $(INCLUDE_PATH)/sources/bark.cpp/build/libbark.a ./
+	$(AR) rcs libbark.a gobark.o
+
+bark-cpp: libbark.a
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH="$(CURDIR)" LIBRARY_PATH=$(CURDIR) \
+	$(GOCMD) build -v -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o bark-cpp ./
+
+package:
+	bash package.sh
+
+build: bark-cpp package
+
+clean:
+	rm -f gobark.o libbark.a

backend/go/bark-cpp/gobark.cpp

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

backend/go/bark-cpp/gobark.go

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

backend/go/bark-cpp/gobark.h

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

backend/go/bark-cpp/main.go

@@ -0,0 +1,20 @@
+package main
+
+// Note: this is started internally by LocalAI and a server is allocated for each model
+import (
+	"flag"
+
+	grpc "github.com/mudler/LocalAI/pkg/grpc"
+)
+
+var (
+	addr = flag.String("addr", "localhost:50051", "the address to connect to")
+)
+
+func main() {
+	flag.Parse()
+
+	if err := grpc.StartServer(*addr, &Bark{}); err != nil {
+		panic(err)
+	}
+}

backend/go/bark-cpp/package.sh

@@ -0,0 +1,41 @@
+#!/bin/bash
+
+# Script to copy the appropriate libraries based on architecture
+# This script is used in the final stage of the Dockerfile
+
+set -e
+
+CURDIR=$(dirname "$(realpath $0)")
+
+# Create lib directory
+mkdir -p $CURDIR/package/lib
+cp -avrf $CURDIR/bark-cpp $CURDIR/package/
+cp -rfv $CURDIR/run.sh $CURDIR/package/
+
+# Detect architecture and copy appropriate libraries
+if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
+    # x86_64 architecture
+    echo "Detected x86_64 architecture, copying x86_64 libraries..."
+    cp -arfLv /lib64/ld-linux-x86-64.so.2 $CURDIR/package/lib/ld.so
+    cp -arfLv /lib/x86_64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
+    cp -arfLv /lib/x86_64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
+    cp -arfLv /lib/x86_64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
+    cp -arfLv /lib/x86_64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
+    cp -arfLv /lib/x86_64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
+elif [ -f "/lib/ld-linux-aarch64.so.1" ]; then
+    # ARM64 architecture
+    echo "Detected ARM64 architecture, copying ARM64 libraries..."
+    cp -arfLv /lib/ld-linux-aarch64.so.1 $CURDIR/package/lib/ld.so
+    cp -arfLv /lib/aarch64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
+    cp -arfLv /lib/aarch64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
+    cp -arfLv /lib/aarch64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
+    cp -arfLv /lib/aarch64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
+    cp -arfLv /lib/aarch64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
+else
+    echo "Error: Could not detect architecture"
+    exit 1
+fi
+
+echo "Packaging completed successfully" 
+ls -liah $CURDIR/package/
+ls -liah $CURDIR/package/lib/

backend/go/bark-cpp/run.sh

@@ -0,0 +1,13 @@
+#!/bin/bash
+set -ex
+
+CURDIR=$(dirname "$(realpath $0)")
+export LD_LIBRARY_PATH=$CURDIR/lib:$LD_LIBRARY_PATH
+
+# If there is a lib/ld.so, use it
+if [ -f $CURDIR/lib/ld.so ]; then
+	echo "Using lib/ld.so"
+	exec $CURDIR/lib/ld.so $CURDIR/bark-cpp "$@"
+fi
+
+exec $CURDIR/bark-cpp "$@"

backend/go/local-store/debug.go

@@ -4,11 +4,11 @@
 package main
 
 import (
-	"github.com/mudler/xlog"
+	"github.com/rs/zerolog/log"
 )
 
 func assert(cond bool, msg string) {
 	if !cond {
-		xlog.Fatal().Stack().Msg(msg)
+		log.Fatal().Stack().Msg(msg)
 	}
 }

backend/go/local-store/main.go

@@ -7,7 +7,8 @@ import (
 	"os"
 
 	grpc "github.com/mudler/LocalAI/pkg/grpc"
-	"github.com/mudler/xlog"
+	"github.com/rs/zerolog"
+	"github.com/rs/zerolog/log"
 )
 
 var (
@@ -15,7 +16,7 @@ var (
 )
 
 func main() {
-	xlog.SetLogger(xlog.NewLogger(xlog.LogLevel(os.Getenv("LOCALAI_LOG_LEVEL")), os.Getenv("LOCALAI_LOG_FORMAT")))
+	log.Logger = log.Output(zerolog.ConsoleWriter{Out: os.Stderr})
 
 	flag.Parse()
 

backend/go/local-store/store.go

@@ -12,7 +12,7 @@ import (
 	"github.com/mudler/LocalAI/pkg/grpc/base"
 	pb "github.com/mudler/LocalAI/pkg/grpc/proto"
 
-	"github.com/mudler/xlog"
+	"github.com/rs/zerolog/log"
 )
 
 type Store struct {
@@ -135,7 +135,7 @@ func (s *Store) StoresSet(opts *pb.StoresSetOptions) error {
 			} else {
 				sample = k.Floats
 			}
-			xlog.Debug("Key is not normalized", "sample", sample)
+			log.Debug().Msgf("Key is not normalized: %v", sample)
 		}
 
 		kvs[i] = Pair{
@@ -238,7 +238,7 @@ func (s *Store) StoresDelete(opts *pb.StoresDeleteOptions) error {
 			assert(!hasKey(s.keys, k), fmt.Sprintf("Key exists, but was not found: t=%d, %v", len(tail_ks), k))
 		}
 
-		xlog.Debug("Delete", "found", found, "tailLen", len(tail_ks), "j", j, "mergeKeysLen", len(merge_ks), "mergeValuesLen", len(merge_vs))
+		log.Debug().Msgf("Delete: found = %v, t = %d, j = %d, len(merge_ks) = %d, len(merge_vs) = %d", found, len(tail_ks), j, len(merge_ks), len(merge_vs))
 	}
 
 	merge_ks = append(merge_ks, tail_ks...)
@@ -261,7 +261,7 @@ func (s *Store) StoresDelete(opts *pb.StoresDeleteOptions) error {
 	}(), "Keys to delete still present")
 
 	if len(s.keys) != l {
-		xlog.Debug("Delete: Some keys not found", "keysLen", len(s.keys), "expectedLen", l)
+		log.Debug().Msgf("Delete: Some keys not found: len(s.keys) = %d, l = %d", len(s.keys), l)
 	}
 
 	return nil
@@ -273,7 +273,7 @@ func (s *Store) StoresGet(opts *pb.StoresGetOptions) (pb.StoresGetResult, error)
 	ks := sortIntoKeySlicese(opts.Keys)
 
 	if len(s.keys) == 0 {
-		xlog.Debug("Get: No keys in store")
+		log.Debug().Msgf("Get: No keys in store")
 	}
 
 	if s.keyLen == -1 {
@@ -305,7 +305,7 @@ func (s *Store) StoresGet(opts *pb.StoresGetOptions) (pb.StoresGetResult, error)
 	}
 
 	if len(pbKeys) != len(opts.Keys) {
-		xlog.Debug("Get: Some keys not found", "pbKeysLen", len(pbKeys), "optsKeysLen", len(opts.Keys), "storeKeysLen", len(s.keys))
+		log.Debug().Msgf("Get: Some keys not found: len(pbKeys) = %d, len(opts.Keys) = %d, len(s.Keys) = %d", len(pbKeys), len(opts.Keys), len(s.keys))
 	}
 
 	return pb.StoresGetResult{
@@ -507,7 +507,7 @@ func (s *Store) StoresFind(opts *pb.StoresFindOptions) (pb.StoresFindResult, err
 			} else {
 				sample = tk
 			}
-			xlog.Debug("Trying to compare non-normalized key with normalized keys", "sample", sample)
+			log.Debug().Msgf("Trying to compare non-normalized key with normalized keys: %v", sample)
 		}
 
 		return s.StoresFindFallback(opts)

backend/go/stablediffusion-ggml/Makefile

@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
 
 # stablediffusion.cpp (ggml)
 STABLEDIFFUSION_GGML_REPO?=https://github.com/leejet/stable-diffusion.cpp
-STABLEDIFFUSION_GGML_VERSION?=e411520407663e1ddf8ff2e5ed4ff3a116fbbc97
+STABLEDIFFUSION_GGML_VERSION?=0ebe6fe118f125665939b27c89f34ed38716bff8
 
 CMAKE_ARGS+=-DGGML_MAX_NAME=128
 
@@ -28,12 +28,7 @@ else ifeq ($(BUILD_TYPE),clblas)
 	CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
 # If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
 else ifeq ($(BUILD_TYPE),hipblas)
-	ROCM_HOME ?= /opt/rocm
-	ROCM_PATH ?= /opt/rocm
-	export CXX=$(ROCM_HOME)/llvm/bin/clang++
-	export CC=$(ROCM_HOME)/llvm/bin/clang
-	AMDGPU_TARGETS?=gfx803,gfx900,gfx906,gfx908,gfx90a,gfx942,gfx1010,gfx1030,gfx1032,gfx1100,gfx1101,gfx1102,gfx1200,gfx1201
-	CMAKE_ARGS+=-DSD_HIPBLAS=ON -DGGML_HIPBLAS=ON -DAMDGPU_TARGETS=$(AMDGPU_TARGETS)
+	CMAKE_ARGS+=-DSD_HIPBLAS=ON -DGGML_HIPBLAS=ON
 else ifeq ($(BUILD_TYPE),vulkan)
 	CMAKE_ARGS+=-DSD_VULKAN=ON -DGGML_VULKAN=ON
 else ifeq ($(OS),Darwin)

backend/go/stablediffusion-ggml/gosd.cpp

@@ -1,5 +1,3 @@
-#include "stable-diffusion.h"
-#include <cmath>
 #include <cstdint>
 #define GGML_MAX_NAME 128
 
@@ -8,9 +6,7 @@
 #include <time.h>
 #include <string>
 #include <vector>
-#include <map>
 #include <filesystem>
-#include <algorithm>
 #include "gosd.h"
 
 #define STB_IMAGE_IMPLEMENTATION
@@ -24,13 +20,11 @@
 #define STB_IMAGE_RESIZE_IMPLEMENTATION
 #define STB_IMAGE_RESIZE_STATIC
 #include "stb_image_resize.h"
-#include <stdlib.h>
-#include <regex>
 
 // Names of the sampler method, same order as enum sample_method in stable-diffusion.h
 const char* sample_method_str[] = {
+    "default",
     "euler",
-    "euler_a",
     "heun",
     "dpm2",
     "dpm++2s_a",
@@ -41,384 +35,29 @@ const char* sample_method_str[] = {
     "lcm",
     "ddim_trailing",
     "tcd",
+    "euler_a",
 };
 
 static_assert(std::size(sample_method_str) == SAMPLE_METHOD_COUNT, "sample method mismatch");
 
 // Names of the sigma schedule overrides, same order as sample_schedule in stable-diffusion.h
 const char* schedulers[] = {
+    "default",
     "discrete",
     "karras",
     "exponential",
     "ays",
     "gits",
-    "sgm_uniform",
-    "simple",
     "smoothstep",
-    "kl_optimal",
-    "lcm",
 };
 
-static_assert(std::size(schedulers) == SCHEDULER_COUNT, "schedulers mismatch");
+static_assert(std::size(schedulers) == SCHEDULE_COUNT, "schedulers mismatch");
 
-// New enum string arrays
-const char* rng_type_str[] = {
-    "std_default",
-    "cuda",
-    "cpu",
-};
-static_assert(std::size(rng_type_str) == RNG_TYPE_COUNT, "rng type mismatch");
-
-const char* prediction_str[] = {
-    "epsilon",
-    "v",
-    "edm_v",
-    "flow",
-    "flux_flow",
-    "flux2_flow",
-};
-static_assert(std::size(prediction_str) == PREDICTION_COUNT, "prediction mismatch");
-
-const char* lora_apply_mode_str[] = {
-    "auto",
-    "immediately",
-    "at_runtime",
-};
-static_assert(std::size(lora_apply_mode_str) == LORA_APPLY_MODE_COUNT, "lora apply mode mismatch");
-
-constexpr const char* sd_type_str[] = {
-    "f32",      // 0
-    "f16",      // 1
-    "q4_0",     // 2
-    "q4_1",     // 3
-    nullptr,    // 4
-    nullptr,    // 5
-    "q5_0",     // 6
-    "q5_1",     // 7
-    "q8_0",     // 8
-    "q8_1",     // 9
-    "q2_k",     // 10
-    "q3_k",     // 11
-    "q4_k",     // 12
-    "q5_k",     // 13
-    "q6_k",     // 14
-    "q8_k",     // 15
-    "iq2_xxs",  // 16
-    "iq2_xs",   // 17
-    "iq3_xxs",  // 18
-    "iq1_s",    // 19
-    "iq4_nl",   // 20
-    "iq3_s",    // 21
-    "iq2_s",    // 22
-    "iq4_xs",   // 23
-    "i8",       // 24
-    "i16",      // 25
-    "i32",      // 26
-    "i64",      // 27
-    "f64",      // 28
-    "iq1_m",    // 29
-    "bf16",     // 30
-    nullptr, nullptr, nullptr, nullptr,  // 31-34
-    "tq1_0",    // 35
-    "tq2_0",    // 36
-    nullptr, nullptr,           // 37-38
-    "mxfp4"     // 39
-};
-static_assert(std::size(sd_type_str) == SD_TYPE_COUNT, "sd type mismatch");
-
-sd_ctx_params_t ctx_params;
 sd_ctx_t* sd_c;
 // Moved from the context (load time) to generation time params
-scheduler_t scheduler = SCHEDULER_COUNT;
-sample_method_t sample_method = SAMPLE_METHOD_COUNT;
+scheduler_t scheduler = scheduler_t::DEFAULT;
 
-// Storage for embeddings (needs to persist for the lifetime of ctx_params)
-static std::vector<sd_embedding_t> embedding_vec;
-// Storage for embedding strings (needs to persist as long as embedding_vec references them)
-static std::vector<std::string> embedding_strings;
-
-// Storage for LoRAs (needs to persist for the lifetime of generation params)
-static std::vector<sd_lora_t> lora_vec;
-// Storage for LoRA strings (needs to persist as long as lora_vec references them)
-static std::vector<std::string> lora_strings;
-// Storage for lora_dir path
-static std::string lora_dir_path;
-
-// Build embeddings vector from directory, similar to upstream CLI
-static void build_embedding_vec(const char* embedding_dir) {
-    embedding_vec.clear();
-    embedding_strings.clear();
-
-    if (!embedding_dir || strlen(embedding_dir) == 0) {
-        return;
-    }
-
-    if (!std::filesystem::exists(embedding_dir) || !std::filesystem::is_directory(embedding_dir)) {
-        fprintf(stderr, "Embedding directory does not exist or is not a directory: %s\n", embedding_dir);
-        return;
-    }
-
-    static const std::vector<std::string> valid_ext = {".pt", ".safetensors", ".gguf"};
-
-    for (const auto& entry : std::filesystem::directory_iterator(embedding_dir)) {
-        if (!entry.is_regular_file()) {
-            continue;
-        }
-
-        auto path = entry.path();
-        std::string ext = path.extension().string();
-
-        bool valid = false;
-        for (const auto& e : valid_ext) {
-            if (ext == e) {
-                valid = true;
-                break;
-            }
-        }
-        if (!valid) {
-            continue;
-        }
-
-        std::string name = path.stem().string();
-        std::string full_path = path.string();
-
-        // Store strings in persistent storage
-        embedding_strings.push_back(name);
-        embedding_strings.push_back(full_path);
-
-        sd_embedding_t item;
-        item.name = embedding_strings[embedding_strings.size() - 2].c_str();
-        item.path = embedding_strings[embedding_strings.size() - 1].c_str();
-
-        embedding_vec.push_back(item);
-        fprintf(stderr, "Found embedding: %s -> %s\n", item.name, item.path);
-    }
-
-    fprintf(stderr, "Loaded %zu embeddings from %s\n", embedding_vec.size(), embedding_dir);
-}
-
-// Discover LoRA files in directory and build a map of name -> path
-static std::map<std::string, std::string> discover_lora_files(const char* lora_dir) {
-    std::map<std::string, std::string> lora_map;
-
-    if (!lora_dir || strlen(lora_dir) == 0) {
-        fprintf(stderr, "LoRA directory not specified\n");
-        return lora_map;
-    }
-
-    if (!std::filesystem::exists(lora_dir) || !std::filesystem::is_directory(lora_dir)) {
-        fprintf(stderr, "LoRA directory does not exist or is not a directory: %s\n", lora_dir);
-        return lora_map;
-    }
-
-    static const std::vector<std::string> valid_ext = {".safetensors", ".ckpt", ".pt", ".gguf"};
-
-    fprintf(stderr, "Discovering LoRA files in: %s\n", lora_dir);
-
-    for (const auto& entry : std::filesystem::directory_iterator(lora_dir)) {
-        if (!entry.is_regular_file()) {
-            continue;
-        }
-
-        auto path = entry.path();
-        std::string ext = path.extension().string();
-
-        bool valid = false;
-        for (const auto& e : valid_ext) {
-            if (ext == e) {
-                valid = true;
-                break;
-            }
-        }
-        if (!valid) {
-            continue;
-        }
-
-        std::string name = path.stem().string();  // stem() already removes extension
-        std::string full_path = path.string();
-
-        // Store the name (without extension) -> full path mapping
-        // This allows users to specify just the name in <lora:name:strength>
-        lora_map[name] = full_path;
-
-        fprintf(stderr, "Found LoRA file: %s -> %s\n", name.c_str(), full_path.c_str());
-    }
-
-    fprintf(stderr, "Discovered %zu LoRA files in %s\n", lora_map.size(), lora_dir);
-    return lora_map;
-}
-
-// Helper function to check if a path is absolute (matches upstream)
-static bool is_absolute_path(const std::string& p) {
-#ifdef _WIN32
-    // Windows: C:/path or C:\path
-    return p.size() > 1 && std::isalpha(static_cast<unsigned char>(p[0])) && p[1] == ':';
-#else
-    // Unix: /path
-    return !p.empty() && p[0] == '/';
-#endif
-}
-
-// Parse LoRAs from prompt string (e.g., "<lora:name:1.0>" or "<lora:name>")
-// Returns a vector of LoRA info and the cleaned prompt with LoRA tags removed
-// Matches upstream implementation more closely
-static std::pair<std::vector<sd_lora_t>, std::string> parse_loras_from_prompt(const std::string& prompt, const char* lora_dir) {
-    std::vector<sd_lora_t> loras;
-    std::string cleaned_prompt = prompt;
-
-    if (!lora_dir || strlen(lora_dir) == 0) {
-        fprintf(stderr, "LoRA directory not set, cannot parse LoRAs from prompt\n");
-        return {loras, cleaned_prompt};
-    }
-
-    // Discover LoRA files for name-based lookup
-    std::map<std::string, std::string> discovered_lora_map = discover_lora_files(lora_dir);
-
-    // Map to accumulate multipliers for the same LoRA (matches upstream)
-    std::map<std::string, float> lora_map;
-    std::map<std::string, float> high_noise_lora_map;
-
-    static const std::regex re(R"(<lora:([^:>]+):([^>]+)>)");
-    static const std::vector<std::string> valid_ext = {".pt", ".safetensors", ".gguf"};
-    std::smatch m;
-
-    std::string tmp = prompt;
-
-    fprintf(stderr, "Parsing LoRAs from prompt: %s\n", prompt.c_str());
-
-    while (std::regex_search(tmp, m, re)) {
-        std::string raw_path = m[1].str();
-        const std::string raw_mul = m[2].str();
-
-        float mul = 0.f;
-        try {
-            mul = std::stof(raw_mul);
-        } catch (...) {
-            tmp = m.suffix().str();
-            cleaned_prompt = std::regex_replace(cleaned_prompt, re, "", std::regex_constants::format_first_only);
-            fprintf(stderr, "Invalid LoRA multiplier '%s', skipping\n", raw_mul.c_str());
-            continue;
-        }
-
-        bool is_high_noise = false;
-        static const std::string prefix = "|high_noise|";
-        if (raw_path.rfind(prefix, 0) == 0) {
-            raw_path.erase(0, prefix.size());
-            is_high_noise = true;
-        }
-
-        std::filesystem::path final_path;
-        if (is_absolute_path(raw_path)) {
-            final_path = raw_path;
-        } else {
-            // Try name-based lookup first
-            auto it = discovered_lora_map.find(raw_path);
-            if (it != discovered_lora_map.end()) {
-                final_path = it->second;
-            } else {
-                // Try case-insensitive lookup
-                bool found = false;
-                for (const auto& pair : discovered_lora_map) {
-                    std::string lower_name = raw_path;
-                    std::string lower_key = pair.first;
-                    std::transform(lower_name.begin(), lower_name.end(), lower_name.begin(), ::tolower);
-                    std::transform(lower_key.begin(), lower_key.end(), lower_key.begin(), ::tolower);
-                    if (lower_name == lower_key) {
-                        final_path = pair.second;
-                        found = true;
-                        break;
-                    }
-                }
-                if (!found) {
-                    // Try as relative path in lora_dir
-                    final_path = std::filesystem::path(lora_dir) / raw_path;
-                }
-            }
-        }
-
-        // Try adding extensions if file doesn't exist
-        if (!std::filesystem::exists(final_path)) {
-            bool found = false;
-            for (const auto& ext : valid_ext) {
-                std::filesystem::path try_path = final_path;
-                try_path += ext;
-                if (std::filesystem::exists(try_path)) {
-                    final_path = try_path;
-                    found = true;
-                    break;
-                }
-            }
-            if (!found) {
-                fprintf(stderr, "WARNING: LoRA file not found: %s\n", final_path.lexically_normal().string().c_str());
-                tmp = m.suffix().str();
-                cleaned_prompt = std::regex_replace(cleaned_prompt, re, "", std::regex_constants::format_first_only);
-                continue;
-            }
-        }
-
-        // Normalize path (matches upstream)
-        const std::string key = final_path.lexically_normal().string();
-
-        // Accumulate multiplier if same LoRA appears multiple times (matches upstream)
-        if (is_high_noise) {
-            high_noise_lora_map[key] += mul;
-        } else {
-            lora_map[key] += mul;
-        }
-
-        fprintf(stderr, "Parsed LoRA: path='%s', multiplier=%.2f, is_high_noise=%s\n",
-                key.c_str(), mul, is_high_noise ? "true" : "false");
-
-        cleaned_prompt = std::regex_replace(cleaned_prompt, re, "", std::regex_constants::format_first_only);
-        tmp = m.suffix().str();
-    }
-
-    // Build final LoRA vector from accumulated maps (matches upstream)
-    // Store all path strings first to ensure they persist
-    for (const auto& kv : lora_map) {
-        lora_strings.push_back(kv.first);
-    }
-    for (const auto& kv : high_noise_lora_map) {
-        lora_strings.push_back(kv.first);
-    }
-
-    // Now build the LoRA vector with pointers to the stored strings
-    size_t string_idx = 0;
-    for (const auto& kv : lora_map) {
-        sd_lora_t item;
-        item.is_high_noise = false;
-        item.path = lora_strings[string_idx].c_str();
-        item.multiplier = kv.second;
-        loras.push_back(item);
-        string_idx++;
-    }
-
-    for (const auto& kv : high_noise_lora_map) {
-        sd_lora_t item;
-        item.is_high_noise = true;
-        item.path = lora_strings[string_idx].c_str();
-        item.multiplier = kv.second;
-        loras.push_back(item);
-        string_idx++;
-    }
-
-    // Clean up extra spaces
-    std::regex space_regex(R"(\s+)");
-    cleaned_prompt = std::regex_replace(cleaned_prompt, space_regex, " ");
-    // Trim leading/trailing spaces
-    size_t first = cleaned_prompt.find_first_not_of(" \t");
-    if (first != std::string::npos) {
-        cleaned_prompt.erase(0, first);
-    }
-    size_t last = cleaned_prompt.find_last_not_of(" \t");
-    if (last != std::string::npos) {
-        cleaned_prompt.erase(last + 1);
-    }
-
-    fprintf(stderr, "Parsed %zu LoRA(s) from prompt. Cleaned prompt: %s\n", loras.size(), cleaned_prompt.c_str());
-
-    return {loras, cleaned_prompt};
-}
+sample_method_t sample_method;
 
 // Copied from the upstream CLI
 static void sd_log_cb(enum sd_log_level_t level, const char* log, void* data) {
@@ -459,7 +98,7 @@ int load_model(const char *model, char *model_path, char* options[], int threads
 
     const char *stableDiffusionModel = "";
     if (diff == 1 ) {
-        stableDiffusionModel = strdup(model);
+        stableDiffusionModel = model;
         model = "";
     }
 
@@ -470,38 +109,8 @@ int load_model(const char *model, char *model_path, char* options[], int threads
     const char *vae_path  = "";
     const char *scheduler_str = "";
     const char *sampler = "";
-    const char *clip_vision_path = "";
-    const char *llm_path = "";
-    const char *llm_vision_path = "";
-    const char *diffusion_model_path = stableDiffusionModel;
-    const char *high_noise_diffusion_model_path = "";
-    const char *taesd_path  = "";
-    const char *control_net_path = "";
-    const char *embedding_dir = "";
-    const char *photo_maker_path = "";
-    const char *tensor_type_rules = "";
     char *lora_dir = model_path;
-
-    bool vae_decode_only = true;
-    int n_threads = threads;
-    enum sd_type_t wtype = SD_TYPE_COUNT;
-    enum rng_type_t rng_type = CUDA_RNG;
-    enum rng_type_t sampler_rng_type = RNG_TYPE_COUNT;
-    enum prediction_t prediction = PREDICTION_COUNT;
-    enum lora_apply_mode_t lora_apply_mode = LORA_APPLY_AUTO;
-    bool offload_params_to_cpu = false;
-    bool keep_clip_on_cpu = false;
-    bool keep_control_net_on_cpu = false;
-    bool keep_vae_on_cpu = false;
-    bool diffusion_flash_attn = false;
-    bool tae_preview_only = false;
-    bool diffusion_conv_direct = false;
-    bool vae_conv_direct = false;
-    bool force_sdxl_vae_conv_scale = false;
-    bool chroma_use_dit_mask = true;
-    bool chroma_use_t5_mask = false;
-    int chroma_t5_mask_pad = 1;
-    float flow_shift = INFINITY;
+    bool lora_dir_allocated = false;
 
     fprintf(stderr, "parsing options: %p\n", options);
 
@@ -514,16 +123,16 @@ int load_model(const char *model, char *model_path, char* options[], int threads
         }
 
         if (!strcmp(optname, "clip_l_path")) {
-            clip_l_path = strdup(optval);
+            clip_l_path = optval;
         }
         if (!strcmp(optname, "clip_g_path")) {
-            clip_g_path = strdup(optval);
+            clip_g_path = optval;
         }
         if (!strcmp(optname, "t5xxl_path")) {
-            t5xxl_path = strdup(optval);
+            t5xxl_path = optval;
         }
         if (!strcmp(optname, "vae_path")) {
-            vae_path = strdup(optval);
+            vae_path = optval;
         }
         if (!strcmp(optname, "scheduler")) {
             scheduler_str = optval;
@@ -538,201 +147,18 @@ int load_model(const char *model, char *model_path, char* options[], int threads
                 std::filesystem::path lora_path(optval);
                 std::filesystem::path full_lora_path = model_path_str / lora_path;
                 lora_dir = strdup(full_lora_path.string().c_str());
-                lora_dir_path = full_lora_path.string();
-                fprintf(stderr, "LoRA dir resolved to: %s\n", lora_dir);
+                lora_dir_allocated = true;
+                fprintf(stderr, "Lora dir resolved to: %s\n", lora_dir);
             } else {
                 lora_dir = strdup(optval);
-                lora_dir_path = std::string(optval);
+                lora_dir_allocated = true;
                 fprintf(stderr, "No model path provided, using lora dir as-is: %s\n", lora_dir);
             }
-            // Discover LoRAs immediately when directory is set
-            if (lora_dir && strlen(lora_dir) > 0) {
-                discover_lora_files(lora_dir);
-            }
-        }
-
-        // New parsing
-        if (!strcmp(optname, "clip_vision_path")) clip_vision_path = strdup(optval);
-        if (!strcmp(optname, "llm_path")) llm_path = strdup(optval);
-        if (!strcmp(optname, "llm_vision_path")) llm_vision_path = strdup(optval);
-        if (!strcmp(optname, "diffusion_model_path")) diffusion_model_path = strdup(optval);
-        if (!strcmp(optname, "high_noise_diffusion_model_path")) high_noise_diffusion_model_path = strdup(optval);
-        if (!strcmp(optname, "taesd_path")) taesd_path = strdup(optval);
-        if (!strcmp(optname, "control_net_path")) control_net_path = strdup(optval);
-        if (!strcmp(optname, "embedding_dir")) {
-            // Path join with model dir
-            if (model_path && strlen(model_path) > 0) {
-                std::filesystem::path model_path_str(model_path);
-                std::filesystem::path embedding_path(optval);
-                std::filesystem::path full_embedding_path = model_path_str / embedding_path;
-                embedding_dir = strdup(full_embedding_path.string().c_str());
-                fprintf(stderr, "Embedding dir resolved to: %s\n", embedding_dir);
-            } else {
-                embedding_dir = strdup(optval);
-                fprintf(stderr, "No model path provided, using embedding dir as-is: %s\n", embedding_dir);
-            }
-        }
-        if (!strcmp(optname, "photo_maker_path")) photo_maker_path = strdup(optval);
-        if (!strcmp(optname, "tensor_type_rules")) tensor_type_rules = strdup(optval);
-
-        if (!strcmp(optname, "vae_decode_only")) vae_decode_only = (strcmp(optval, "true") == 0 || strcmp(optval, "1") == 0);
-        if (!strcmp(optname, "offload_params_to_cpu")) offload_params_to_cpu = (strcmp(optval, "true") == 0 || strcmp(optval, "1") == 0);
-        if (!strcmp(optname, "keep_clip_on_cpu")) keep_clip_on_cpu = (strcmp(optval, "true") == 0 || strcmp(optval, "1") == 0);
-        if (!strcmp(optname, "keep_control_net_on_cpu")) keep_control_net_on_cpu = (strcmp(optval, "true") == 0 || strcmp(optval, "1") == 0);
-        if (!strcmp(optname, "keep_vae_on_cpu")) keep_vae_on_cpu = (strcmp(optval, "true") == 0 || strcmp(optval, "1") == 0);
-        if (!strcmp(optname, "diffusion_flash_attn")) diffusion_flash_attn = (strcmp(optval, "true") == 0 || strcmp(optval, "1") == 0);
-        if (!strcmp(optname, "tae_preview_only")) tae_preview_only = (strcmp(optval, "true") == 0 || strcmp(optval, "1") == 0);
-        if (!strcmp(optname, "diffusion_conv_direct")) diffusion_conv_direct = (strcmp(optval, "true") == 0 || strcmp(optval, "1") == 0);
-        if (!strcmp(optname, "vae_conv_direct")) vae_conv_direct = (strcmp(optval, "true") == 0 || strcmp(optval, "1") == 0);
-        if (!strcmp(optname, "force_sdxl_vae_conv_scale")) force_sdxl_vae_conv_scale = (strcmp(optval, "true") == 0 || strcmp(optval, "1") == 0);
-        if (!strcmp(optname, "chroma_use_dit_mask")) chroma_use_dit_mask = (strcmp(optval, "true") == 0 || strcmp(optval, "1") == 0);
-        if (!strcmp(optname, "chroma_use_t5_mask")) chroma_use_t5_mask = (strcmp(optval, "true") == 0 || strcmp(optval, "1") == 0);
-
-        if (!strcmp(optname, "n_threads")) n_threads = atoi(optval);
-        if (!strcmp(optname, "chroma_t5_mask_pad")) chroma_t5_mask_pad = atoi(optval);
-
-        if (!strcmp(optname, "flow_shift")) flow_shift = atof(optval);
-
-        if (!strcmp(optname, "rng_type")) {
-            int found = -1;
-            for (int m = 0; m < RNG_TYPE_COUNT; m++) {
-                if (!strcmp(optval, rng_type_str[m])) {
-                    found = m;
-                    break;
-                }
-            }
-            if (found != -1) {
-                rng_type = (rng_type_t)found;
-                fprintf(stderr, "Found rng_type: %s\n", optval);
-            } else {
-                fprintf(stderr, "Invalid rng_type: %s, using default\n", optval);
-            }
-        }
-        if (!strcmp(optname, "sampler_rng_type")) {
-            int found = -1;
-            for (int m = 0; m < RNG_TYPE_COUNT; m++) {
-                if (!strcmp(optval, rng_type_str[m])) {
-                    found = m;
-                    break;
-                }
-            }
-            if (found != -1) {
-                sampler_rng_type = (rng_type_t)found;
-                fprintf(stderr, "Found sampler_rng_type: %s\n", optval);
-            } else {
-                fprintf(stderr, "Invalid sampler_rng_type: %s, using default\n", optval);
-            }
-        }
-        if (!strcmp(optname, "prediction")) {
-            int found = -1;
-            for (int m = 0; m < PREDICTION_COUNT; m++) {
-                if (!strcmp(optval, prediction_str[m])) {
-                    found = m;
-                    break;
-                }
-            }
-            if (found != -1) {
-                prediction = (prediction_t)found;
-                fprintf(stderr, "Found prediction: %s\n", optval);
-            } else {
-                fprintf(stderr, "Invalid prediction: %s, using default\n", optval);
-            }
-        }
-        if (!strcmp(optname, "lora_apply_mode")) {
-            int found = -1;
-            for (int m = 0; m < LORA_APPLY_MODE_COUNT; m++) {
-                if (!strcmp(optval, lora_apply_mode_str[m])) {
-                    found = m;
-                    break;
-                }
-            }
-            if (found != -1) {
-                lora_apply_mode = (lora_apply_mode_t)found;
-                fprintf(stderr, "Found lora_apply_mode: %s\n", optval);
-            } else {
-                fprintf(stderr, "Invalid lora_apply_mode: %s, using default\n", optval);
-            }
-        }
-        if (!strcmp(optname, "wtype")) {
-            int found = -1;
-            for (int m = 0; m < SD_TYPE_COUNT; m++) {
-                if (sd_type_str[m] && !strcmp(optval, sd_type_str[m])) {
-                    found = m;
-                    break;
-                }
-            }
-            if (found != -1) {
-                wtype = (sd_type_t)found;
-                fprintf(stderr, "Found wtype: %s\n", optval);
-            } else {
-                fprintf(stderr, "Invalid wtype: %s, using default\n", optval);
-            }
         }
     }
 
     fprintf(stderr, "parsed options\n");
 
-    // Build embeddings vector from directory if provided
-    build_embedding_vec(embedding_dir);
-
-    fprintf (stderr, "Creating context\n");
-    sd_ctx_params_init(&ctx_params);
-    ctx_params.model_path = model;
-    ctx_params.clip_l_path = clip_l_path;
-    ctx_params.clip_g_path = clip_g_path;
-    ctx_params.clip_vision_path = clip_vision_path;
-    ctx_params.t5xxl_path = t5xxl_path;
-    ctx_params.llm_path = llm_path;
-    ctx_params.llm_vision_path = llm_vision_path;
-    ctx_params.diffusion_model_path = diffusion_model_path;
-    ctx_params.high_noise_diffusion_model_path = high_noise_diffusion_model_path;
-    ctx_params.vae_path = vae_path;
-    ctx_params.taesd_path = taesd_path;
-    ctx_params.control_net_path = control_net_path;
-    if (lora_dir && strlen(lora_dir) > 0) {
-        lora_dir_path = std::string(lora_dir);
-        fprintf(stderr, "LoRA model directory set to: %s\n", lora_dir);
-        // Discover LoRAs at load time for logging
-        discover_lora_files(lora_dir);
-    } else {
-        fprintf(stderr, "WARNING: LoRA model directory not set. LoRAs in prompts will not be loaded.\n");
-    }
-    // Set embeddings array and count
-    ctx_params.embeddings = embedding_vec.empty() ? NULL : embedding_vec.data();
-    ctx_params.embedding_count = static_cast<uint32_t>(embedding_vec.size());
-    ctx_params.photo_maker_path = photo_maker_path;
-    ctx_params.tensor_type_rules = tensor_type_rules;
-    ctx_params.vae_decode_only = vae_decode_only;
-    // XXX: Setting to true causes a segfault on the second run
-    ctx_params.free_params_immediately = false;
-    ctx_params.n_threads = n_threads;
-    ctx_params.rng_type = rng_type;
-    ctx_params.keep_clip_on_cpu = keep_clip_on_cpu;
-    if (wtype != SD_TYPE_COUNT) ctx_params.wtype = wtype;
-    if (sampler_rng_type != RNG_TYPE_COUNT) ctx_params.sampler_rng_type = sampler_rng_type;
-    if (prediction != PREDICTION_COUNT) ctx_params.prediction = prediction;
-    if (lora_apply_mode != LORA_APPLY_MODE_COUNT) ctx_params.lora_apply_mode = lora_apply_mode;
-    ctx_params.offload_params_to_cpu = offload_params_to_cpu;
-    ctx_params.keep_control_net_on_cpu = keep_control_net_on_cpu;
-    ctx_params.keep_vae_on_cpu = keep_vae_on_cpu;
-    ctx_params.diffusion_flash_attn = diffusion_flash_attn;
-    ctx_params.tae_preview_only = tae_preview_only;
-    ctx_params.diffusion_conv_direct = diffusion_conv_direct;
-    ctx_params.vae_conv_direct = vae_conv_direct;
-    ctx_params.force_sdxl_vae_conv_scale = force_sdxl_vae_conv_scale;
-    ctx_params.chroma_use_dit_mask = chroma_use_dit_mask;
-    ctx_params.chroma_use_t5_mask = chroma_use_t5_mask;
-    ctx_params.chroma_t5_mask_pad = chroma_t5_mask_pad;
-    ctx_params.flow_shift = flow_shift;
-    sd_ctx_t* sd_ctx = new_sd_ctx(&ctx_params);
-
-    if (sd_ctx == NULL) {
-        fprintf (stderr, "failed loading model (generic error)\n");
-        // TODO: Clean up allocated memory
-        return 1;
-    }
-    fprintf (stderr, "Created context: OK\n");
-
     int sample_method_found = -1;
     for (int m = 0; m < SAMPLE_METHOD_COUNT; m++) {
         if (!strcmp(sampler, sample_method_str[m])) {
@@ -741,24 +167,54 @@ int load_model(const char *model, char *model_path, char* options[], int threads
         }
     }
     if (sample_method_found == -1) {
-        sample_method_found = sd_get_default_sample_method(sd_ctx);
-        fprintf(stderr, "Invalid sample method, using default: %s\n", sample_method_str[sample_method_found]);
+        fprintf(stderr, "Invalid sample method, default to EULER_A!\n");
+        sample_method_found = sample_method_t::SAMPLE_METHOD_DEFAULT;
     }
     sample_method = (sample_method_t)sample_method_found;
 
-    for (int d = 0; d < SCHEDULER_COUNT; d++) {
+    for (int d = 0; d < SCHEDULE_COUNT; d++) {
         if (!strcmp(scheduler_str, schedulers[d])) {
             scheduler = (scheduler_t)d;
             fprintf (stderr, "Found scheduler: %s\n", scheduler_str);
         }
     }
-    if (scheduler == SCHEDULER_COUNT) {
-      scheduler = sd_get_default_scheduler(sd_ctx, sample_method);
-      fprintf(stderr, "Invalid scheduler, using default: %s\n", schedulers[scheduler]);
+
+    fprintf (stderr, "Creating context\n");
+    sd_ctx_params_t ctx_params;
+    sd_ctx_params_init(&ctx_params);
+    ctx_params.model_path = model;
+    ctx_params.clip_l_path = clip_l_path;
+    ctx_params.clip_g_path = clip_g_path;
+    ctx_params.t5xxl_path = t5xxl_path;
+    ctx_params.diffusion_model_path = stableDiffusionModel;
+    ctx_params.vae_path = vae_path;
+    ctx_params.taesd_path = "";
+    ctx_params.control_net_path = "";
+    ctx_params.lora_model_dir = lora_dir;
+    ctx_params.embedding_dir = "";
+    ctx_params.vae_decode_only = false;
+    ctx_params.free_params_immediately = false;
+    ctx_params.n_threads = threads;
+    ctx_params.rng_type = STD_DEFAULT_RNG;
+    sd_ctx_t* sd_ctx = new_sd_ctx(&ctx_params);
+
+    if (sd_ctx == NULL) {
+        fprintf (stderr, "failed loading model (generic error)\n");
+        // Clean up allocated memory
+        if (lora_dir_allocated && lora_dir) {
+            free(lora_dir);
+        }
+        return 1;
     }
+    fprintf (stderr, "Created context: OK\n");
 
     sd_c = sd_ctx;
 
+    // Clean up allocated memory
+    if (lora_dir_allocated && lora_dir) {
+        free(lora_dir);
+    }
+
     return 0;
 }
 
@@ -787,66 +243,12 @@ sd_tiling_params_t* sd_img_gen_params_get_vae_tiling_params(sd_img_gen_params_t
 sd_img_gen_params_t* sd_img_gen_params_new(void) {
     sd_img_gen_params_t *params = (sd_img_gen_params_t *)std::malloc(sizeof(sd_img_gen_params_t));
     sd_img_gen_params_init(params);
-    sd_sample_params_init(&params->sample_params);
-    sd_cache_params_init(&params->cache);
-    params->control_strength = 0.9f;
     return params;
 }
 
-// Storage for cleaned prompt strings (needs to persist)
-static std::string cleaned_prompt_storage;
-static std::string cleaned_negative_prompt_storage;
-
 void sd_img_gen_params_set_prompts(sd_img_gen_params_t *params, const char *prompt, const char *negative_prompt) {
-    // Clear previous LoRA data
-    lora_vec.clear();
-    lora_strings.clear();
-
-    // Parse LoRAs from prompt
-    std::string prompt_str = prompt ? prompt : "";
-    std::string negative_prompt_str = negative_prompt ? negative_prompt : "";
-
-    // Get lora_dir from ctx_params if available, otherwise use stored path
-    const char* lora_dir_to_use = lora_dir_path.empty() ? nullptr : lora_dir_path.c_str();
-
-    auto [loras, cleaned_prompt] = parse_loras_from_prompt(prompt_str, lora_dir_to_use);
-    lora_vec = loras;
-    cleaned_prompt_storage = cleaned_prompt;
-
-    // Also check negative prompt for LoRAs (though this is less common)
-    auto [neg_loras, cleaned_negative] = parse_loras_from_prompt(negative_prompt_str, lora_dir_to_use);
-    // Merge negative prompt LoRAs (though typically not used)
-    if (!neg_loras.empty()) {
-        fprintf(stderr, "Note: Found %zu LoRAs in negative prompt (may not be supported)\n", neg_loras.size());
-    }
-    cleaned_negative_prompt_storage = cleaned_negative;
-
-    // Set the cleaned prompts
-    params->prompt = cleaned_prompt_storage.c_str();
-    params->negative_prompt = cleaned_negative_prompt_storage.c_str();
-
-    // Set LoRAs in params
-    params->loras = lora_vec.empty() ? nullptr : lora_vec.data();
-    params->lora_count = static_cast<uint32_t>(lora_vec.size());
-
-    fprintf(stderr, "Set prompts with %zu LoRAs. Original prompt: %s\n", lora_vec.size(), prompt ? prompt : "(null)");
-    fprintf(stderr, "Cleaned prompt: %s\n", cleaned_prompt_storage.c_str());
-
-    // Debug: Verify LoRAs are set correctly
-    if (params->loras && params->lora_count > 0) {
-        fprintf(stderr, "DEBUG: LoRAs set in params structure:\n");
-        for (uint32_t i = 0; i < params->lora_count; i++) {
-            fprintf(stderr, "  params->loras[%u]: path='%s' (ptr=%p), multiplier=%.2f, is_high_noise=%s\n",
-                    i,
-                    params->loras[i].path ? params->loras[i].path : "(null)",
-                    (void*)params->loras[i].path,
-                    params->loras[i].multiplier,
-                    params->loras[i].is_high_noise ? "true" : "false");
-        }
-    } else {
-        fprintf(stderr, "DEBUG: No LoRAs set in params structure (loras=%p, lora_count=%u)\n",
-                (void*)params->loras, params->lora_count);
-    }
+    params->prompt = prompt;
+    params->negative_prompt = negative_prompt;
 }
 
 void sd_img_gen_params_set_dimensions(sd_img_gen_params_t *params, int width, int height) {
@@ -858,7 +260,7 @@ void sd_img_gen_params_set_seed(sd_img_gen_params_t *params, int64_t seed) {
     params->seed = seed;
 }
 
-int gen_image(sd_img_gen_params_t *p, int steps, char *dst, float cfg_scale, char *src_image, float strength, char *mask_image, char* ref_images[], int ref_images_count) {
+int gen_image(sd_img_gen_params_t *p, int steps, char *dst, float cfg_scale, char *src_image, float strength, char *mask_image, char **ref_images, int ref_images_count) {
 
     sd_image_t* results;
 
@@ -1038,24 +440,6 @@ int gen_image(sd_img_gen_params_t *p, int steps, char *dst, float cfg_scale, cha
         }
     }
 
-    // Log LoRA information
-    if (p->loras && p->lora_count > 0) {
-        fprintf(stderr, "Using %u LoRA(s) in generation:\n", p->lora_count);
-        for (uint32_t i = 0; i < p->lora_count; i++) {
-            fprintf(stderr, "  LoRA[%u]: path='%s', multiplier=%.2f, is_high_noise=%s\n",
-                    i,
-                    p->loras[i].path ? p->loras[i].path : "(null)",
-                    p->loras[i].multiplier,
-                    p->loras[i].is_high_noise ? "true" : "false");
-        }
-    } else {
-        fprintf(stderr, "No LoRAs specified for this generation\n");
-    }
-
-    fprintf(stderr, "Generating image with params: \nctx\n---\n%s\ngen\n---\n%s\n",
-            sd_ctx_params_to_str(&ctx_params),
-            sd_img_gen_params_to_str(p));
-
     results = generate_image(sd_c, p);
 
     std::free(p);
@@ -1088,12 +472,9 @@ int gen_image(sd_img_gen_params_t *p, int steps, char *dst, float cfg_scale, cha
     fprintf (stderr, "Channel: %d\n", results[0].channel);
     fprintf (stderr, "Data: %p\n", results[0].data);
 
-    int ret = stbi_write_png(dst, results[0].width, results[0].height, results[0].channel,
-                             results[0].data, 0, NULL);
-    if (ret)
-      fprintf (stderr, "Saved resulting image to '%s'\n", dst);
-    else
-      fprintf(stderr, "Failed to write image to '%s'\n", dst);
+    stbi_write_png(dst, results[0].width, results[0].height, results[0].channel,
+                       results[0].data, 0, NULL);
+    fprintf (stderr, "Saved resulting image to '%s'\n", dst);
 
     // Clean up
     free(results[0].data);
@@ -1104,14 +485,12 @@ int gen_image(sd_img_gen_params_t *p, int steps, char *dst, float cfg_scale, cha
     for (auto buffer : ref_image_buffers) {
         if (buffer) free(buffer);
     }
-    fprintf (stderr, "gen_image is done: %s\n", dst);
-    fflush(stderr);
+    fprintf (stderr, "gen_image is done: %s", dst);
 
-    return !ret;
+    return 0;
 }
 
 int unload() {
     free_sd_ctx(sd_c);
     return 0;
 }
-

backend/go/stablediffusion-ggml/gosd.go

@@ -22,7 +22,7 @@ type SDGGML struct {
 
 var (
 	LoadModel func(model, model_apth string, options []uintptr, threads int32, diff int) int
-	GenImage  func(params uintptr, steps int, dst string, cfgScale float32, srcImage string, strength float32, maskImage string, refImages []uintptr, refImagesCount int) int
+	GenImage  func(params uintptr, steps int, dst string, cfgScale float32, srcImage string, strength float32, maskImage string, refImages []string, refImagesCount int) int
 
 	TilingParamsSetEnabled       func(params uintptr, enabled bool)
 	TilingParamsSetTileSizes     func(params uintptr, tileSizeX int, tileSizeY int)
@@ -95,12 +95,12 @@ func (sd *SDGGML) Load(opts *pb.ModelOptions) error {
 	sd.cfgScale = opts.CFGScale
 
 	ret := LoadModel(modelFile, modelPathC, options, opts.Threads, diffusionModel)
-	runtime.KeepAlive(keepAlive)
-	fmt.Fprintf(os.Stderr, "LoadModel: %d\n", ret)
 	if ret != 0 {
 		return fmt.Errorf("could not load model")
 	}
 
+	runtime.KeepAlive(keepAlive)
+
 	return nil
 }
 
@@ -123,15 +123,10 @@ func (sd *SDGGML) GenerateImage(opts *pb.GenerateImageRequest) error {
 		}
 	}
 
-	// At the time of writing Purego doesn't recurse into slices and convert Go strings to pointers so we need to do that
-	var keepAlive []any
 	refImagesCount := len(opts.RefImages)
-	refImages := make([]uintptr, refImagesCount, refImagesCount+1)
-	for i, ri := range opts.RefImages {
-		bytep := CString(ri)
-		refImages[i] = uintptr(unsafe.Pointer(bytep))
-		keepAlive = append(keepAlive, bytep)
-	}
+	refImages := make([]string, refImagesCount, refImagesCount+1)
+	copy(refImages, opts.RefImages)
+	*(*uintptr)(unsafe.Add(unsafe.Pointer(&refImages), refImagesCount)) = 0
 
 	// Default strength for img2img (0.75 is a good default)
 	strength := float32(0.75)
@@ -145,8 +140,6 @@ func (sd *SDGGML) GenerateImage(opts *pb.GenerateImageRequest) error {
 	TilingParamsSetEnabled(vaep, false)
 
 	ret := GenImage(p, int(opts.Step), dst, sd.cfgScale, srcImage, strength, maskImage, refImages, refImagesCount)
-	runtime.KeepAlive(keepAlive)
-	fmt.Fprintf(os.Stderr, "GenImage: %d\n", ret)
 	if ret != 0 {
 		return fmt.Errorf("inference failed")
 	}

backend/go/stablediffusion-ggml/gosd.h

@@ -17,7 +17,7 @@ void sd_img_gen_params_set_dimensions(sd_img_gen_params_t *params, int width, in
 void sd_img_gen_params_set_seed(sd_img_gen_params_t *params, int64_t seed);
 
 int load_model(const char *model, char *model_path, char* options[], int threads, int diffusionModel);
-int gen_image(sd_img_gen_params_t *p, int steps, char *dst, float cfg_scale, char *src_image, float strength, char *mask_image, char* ref_images[], int ref_images_count);
+int gen_image(sd_img_gen_params_t *p, int steps, char *dst, float cfg_scale, char *src_image, float strength, char *mask_image, char **ref_images, int ref_images_count);
 #ifdef __cplusplus
 }
 #endif

backend/go/stablediffusion-ggml/package.sh

@@ -6,7 +6,6 @@
 set -e
 
 CURDIR=$(dirname "$(realpath $0)")
-REPO_ROOT="${CURDIR}/../../.."
 
 # Create lib directory
 mkdir -p $CURDIR/package/lib
@@ -51,15 +50,6 @@ else
     exit 1
 fi
 
-# Package GPU libraries based on BUILD_TYPE
-# The GPU library packaging script will detect BUILD_TYPE and copy appropriate GPU libraries
-GPU_LIB_SCRIPT="${REPO_ROOT}/scripts/build/package-gpu-libs.sh"
-if [ -f "$GPU_LIB_SCRIPT" ]; then
-    echo "Packaging GPU libraries for BUILD_TYPE=${BUILD_TYPE:-cpu}..."
-    source "$GPU_LIB_SCRIPT" "$CURDIR/package/lib"
-    package_gpu_libs
-fi
-
 echo "Packaging completed successfully"
 ls -liah $CURDIR/package/
 ls -liah $CURDIR/package/lib/

backend/go/whisper/.gitignore

@@ -3,5 +3,5 @@ sources/
 build/
 package/
 whisper
-*.so
-compile_commands.json
+libgowhisper.so
+

backend/go/whisper/Makefile

@@ -8,8 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
 
 # whisper.cpp version
 WHISPER_REPO?=https://github.com/ggml-org/whisper.cpp
-WHISPER_CPP_VERSION?=aa1bc0d1a6dfd70dbb9f60c11df12441e03a9075
-SO_TARGET?=libgowhisper.so
+WHISPER_CPP_VERSION?=edea8a9c3cf0eb7676dcdb604991eb2f95c3d984
 
 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

backend/go/whisper/gowhisper.cpp

@@ -107,7 +107,7 @@ int vad(float pcmf32[], size_t pcmf32_len, float **segs_out,
 }
 
 int transcribe(uint32_t threads, char *lang, bool translate, bool tdrz,
-               float pcmf32[], size_t pcmf32_len, size_t *segs_out_len, char *prompt) {
+               float pcmf32[], size_t pcmf32_len, size_t *segs_out_len) {
   whisper_full_params wparams =
       whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
 
@@ -122,10 +122,8 @@ int transcribe(uint32_t threads, char *lang, bool translate, bool tdrz,
   wparams.debug_mode = true;
   wparams.print_progress = true;
   wparams.tdrz_enable = tdrz;
-  wparams.initial_prompt = prompt;
 
   fprintf(stderr, "info: Enable tdrz: %d\n", tdrz);
-  fprintf(stderr, "info: Initial prompt: \"%s\"\n", prompt);
 
   if (whisper_full(ctx, wparams, pcmf32, pcmf32_len)) {
     fprintf(stderr, "error: transcription failed\n");

backend/go/whisper/gowhisper.go

@@ -17,7 +17,7 @@ var (
 	CppLoadModel                 func(modelPath string) int
 	CppLoadModelVAD              func(modelPath string) int
 	CppVAD                       func(pcmf32 []float32, pcmf32Size uintptr, segsOut unsafe.Pointer, segsOutLen unsafe.Pointer) int
-	CppTranscribe                func(threads uint32, lang string, translate bool, diarize bool, pcmf32 []float32, pcmf32Len uintptr, segsOutLen unsafe.Pointer, prompt string) int
+	CppTranscribe                func(threads uint32, lang string, translate bool, diarize bool, pcmf32 []float32, pcmf32Len uintptr, segsOutLen unsafe.Pointer) int
 	CppGetSegmentText            func(i int) string
 	CppGetSegmentStart           func(i int) int64
 	CppGetSegmentEnd             func(i int) int64
@@ -123,16 +123,15 @@ func (w *Whisper) AudioTranscription(opts *pb.TranscriptRequest) (pb.TranscriptR
 	segsLen := uintptr(0xdeadbeef)
 	segsLenPtr := unsafe.Pointer(&segsLen)
 
-	if ret := CppTranscribe(opts.Threads, opts.Language, opts.Translate, opts.Diarize, data, uintptr(len(data)), segsLenPtr, opts.Prompt); ret != 0 {
+	if ret := CppTranscribe(opts.Threads, opts.Language, opts.Translate, opts.Diarize, data, uintptr(len(data)), segsLenPtr); ret != 0 {
 		return pb.TranscriptResult{}, fmt.Errorf("Failed Transcribe")
 	}
 
 	segments := []*pb.TranscriptSegment{}
 	text := ""
 	for i := range int(segsLen) {
-		// segment start/end conversion factor taken from https://github.com/ggml-org/whisper.cpp/blob/master/examples/cli/cli.cpp#L895
-		s := CppGetSegmentStart(i) * (10000000)
-		t := CppGetSegmentEnd(i) * (10000000)
+		s := CppGetSegmentStart(i)
+		t := CppGetSegmentEnd(i)
 		txt := strings.Clone(CppGetSegmentText(i))
 		tokens := make([]int32, CppNTokens(i))
 

backend/go/whisper/gowhisper.h

@@ -7,8 +7,7 @@ int load_model_vad(const char *const model_path);
 int vad(float pcmf32[], size_t pcmf32_size, float **segs_out,
         size_t *segs_out_len);
 int transcribe(uint32_t threads, char *lang, bool translate, bool tdrz,
-               float pcmf32[], size_t pcmf32_len, size_t *segs_out_len,
-               char *prompt);
+               float pcmf32[], size_t pcmf32_len, size_t *segs_out_len);
 const char *get_segment_text(int i);
 int64_t get_segment_t0(int i);
 int64_t get_segment_t1(int i);

backend/go/whisper/main.go

@@ -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)
 	}

backend/go/whisper/package.sh

@@ -6,13 +6,11 @@
 set -e
 
 CURDIR=$(dirname "$(realpath $0)")
-REPO_ROOT="${CURDIR}/../../.."
 
 # 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
@@ -51,15 +49,6 @@ else
     exit 1
 fi
 
-# Package GPU libraries based on BUILD_TYPE
-# The GPU library packaging script will detect BUILD_TYPE and copy appropriate GPU libraries
-GPU_LIB_SCRIPT="${REPO_ROOT}/scripts/build/package-gpu-libs.sh"
-if [ -f "$GPU_LIB_SCRIPT" ]; then
-    echo "Packaging GPU libraries for BUILD_TYPE=${BUILD_TYPE:-cpu}..."
-    source "$GPU_LIB_SCRIPT" "$CURDIR/package/lib"
-    package_gpu_libs
-fi
-
 echo "Packaging completed successfully"
 ls -liah $CURDIR/package/
 ls -liah $CURDIR/package/lib/

backend/go/whisper/run.sh

@@ -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 $CURDIR/whisper "$@"

backend/python/README.md

@@ -16,8 +16,10 @@ The Python backends use a unified build system based on `libbackend.sh` that pro
 - **transformers** - Hugging Face Transformers framework (PyTorch-based)
 - **vllm** - High-performance LLM inference engine
 - **mlx** - Apple Silicon optimized ML framework
+- **exllama2** - ExLlama2 quantized models
 
 ### Audio & Speech
+- **bark** - Text-to-speech synthesis
 - **coqui** - Coqui TTS models
 - **faster-whisper** - Fast Whisper speech recognition
 - **kitten-tts** - Lightweight TTS
@@ -83,7 +85,7 @@ runUnittests
 The build system automatically detects and configures for different hardware:
 
 - **CPU** - Standard CPU-only builds
-- **CUDA** - NVIDIA GPU acceleration (supports CUDA 12/13)
+- **CUDA** - NVIDIA GPU acceleration (supports CUDA 11/12)
 - **Intel** - Intel XPU/GPU optimization
 - **MLX** - Apple Silicon (M1/M2/M3) optimization
 - **HIP** - AMD GPU acceleration
@@ -93,8 +95,8 @@ The build system automatically detects and configures for different hardware:
 Backends can specify hardware-specific dependencies:
 - `requirements.txt` - Base requirements
 - `requirements-cpu.txt` - CPU-specific packages
+- `requirements-cublas11.txt` - CUDA 11 packages
 - `requirements-cublas12.txt` - CUDA 12 packages
-- `requirements-cublas13.txt` - CUDA 13 packages
 - `requirements-intel.txt` - Intel-optimized packages
 - `requirements-mps.txt` - Apple Silicon packages
 

backend/python/bark/Makefile

@@ -1,18 +1,18 @@
-.PHONY: neutts
-neutts:
+.PHONY: ttsbark
+ttsbark:
 	bash install.sh
 
 .PHONY: run
-run: neutts
-	@echo "Running neutts..."
+run: ttsbark
+	@echo "Running bark..."
 	bash run.sh
-	@echo "neutts run."
+	@echo "bark run."
 
 .PHONY: test
-test: neutts
-	@echo "Testing neutts..."
+test: ttsbark
+	@echo "Testing bark..."
 	bash test.sh
-	@echo "neutts tested."
+	@echo "bark tested."
 
 .PHONY: protogen-clean
 protogen-clean:

backend/python/bark/README.md

@@ -0,0 +1,16 @@
+# Creating a separate environment for ttsbark project
+
+```
+make ttsbark
+```
+
+# Testing the gRPC server
+
+```
+<The path of your python interpreter> -m unittest test_ttsbark.py
+```
+
+For example
+```
+/opt/conda/envs/bark/bin/python -m unittest extra/grpc/bark/test_ttsbark.py
+``````

backend/python/bark/backend.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 """
-This is an extra gRPC server of LocalAI for Moonshine transcription
+This is an extra gRPC server of LocalAI for Bark TTS
 """
 from concurrent import futures
 import time
@@ -8,9 +8,11 @@ import argparse
 import signal
 import sys
 import os
+from scipy.io.wavfile import write as write_wav
+
 import backend_pb2
 import backend_pb2_grpc
-import moonshine_onnx
+from bark import SAMPLE_RATE, generate_audio, preload_models
 
 import grpc
 
@@ -27,52 +29,36 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
     """
     def Health(self, request, context):
         return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
-    
     def LoadModel(self, request, context):
+        model_name = request.Model
         try:
             print("Preparing models, please wait", file=sys.stderr)
-            # Store the model name for use in transcription
-            # Model name format: e.g., "moonshine/tiny"
-            self.model_name = request.Model
-            print(f"Model name set to: {self.model_name}", file=sys.stderr)
+            # download and load all models
+            preload_models()
         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 AudioTranscription(self, request, context):
-        resultSegments = []
-        text = ""
+    def TTS(self, request, context):
+        model = request.model
+        print(request, file=sys.stderr)
         try:
-            # moonshine_onnx.transcribe returns a list of strings
-            transcriptions = moonshine_onnx.transcribe(request.dst, self.model_name)
-            
-            # Combine all transcriptions into a single text
-            if isinstance(transcriptions, list):
-                text = " ".join(transcriptions)
-                # Create segments for each transcription in the list
-                for id, trans in enumerate(transcriptions):
-                    # Since moonshine doesn't provide timing info, we'll create a single segment
-                    # with id and text, using approximate timing
-                    resultSegments.append(backend_pb2.TranscriptSegment(
-                        id=id, 
-                        start=0, 
-                        end=0, 
-                        text=trans
-                    ))
+            audio_array = None
+            if model != "":
+                audio_array = generate_audio(request.text, history_prompt=model)
             else:
-                # Handle case where it's not a list (shouldn't happen, but be safe)
-                text = str(transcriptions)
-                resultSegments.append(backend_pb2.TranscriptSegment(
-                    id=0,
-                    start=0,
-                    end=0,
-                    text=text
-                ))
+                audio_array = generate_audio(request.text)
+            print("saving to", request.dst, file=sys.stderr)
+            # save audio to disk
+            write_wav(request.dst, SAMPLE_RATE, audio_array)
+            print("saved to", request.dst, file=sys.stderr)
+            print("tts for", file=sys.stderr)
+            print(request, file=sys.stderr)
         except Exception as err:
-            print(f"Unexpected {err=}, {type(err)=}", file=sys.stderr)
-            return backend_pb2.TranscriptResult(segments=[], text="")
-
-        return backend_pb2.TranscriptResult(segments=resultSegments, text=text)
+            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),
@@ -110,4 +96,3 @@ if __name__ == "__main__":
     args = parser.parse_args()
 
     serve(args.addr)
-

backend/python/bark/install.sh

@@ -16,15 +16,4 @@ if [ "x${BUILD_PROFILE}" == "xintel" ]; then
     EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
 fi
 
-# Use python 3.12 for l4t
-if [ "x${BUILD_PROFILE}" == "xl4t13" ]; then
-  PYTHON_VERSION="3.12"
-  PYTHON_PATCH="12"
-  PY_STANDALONE_TAG="20251120"
-fi
-
-if [ "x${BUILD_PROFILE}" == "xl4t12" ]; then
-    USE_PIP=true
-fi
-
 installRequirements

backend/python/bark/requirements-cpu.txt

@@ -0,0 +1,4 @@
+transformers
+accelerate
+torch==2.4.1
+torchaudio==2.4.1

backend/python/bark/requirements-cublas11.txt

@@ -0,0 +1,5 @@
+--extra-index-url https://download.pytorch.org/whl/cu118
+torch==2.4.1+cu118
+torchaudio==2.4.1+cu118
+transformers
+accelerate

backend/python/bark/requirements-cublas12.txt

@@ -0,0 +1,4 @@
+torch==2.4.1
+torchaudio==2.4.1
+transformers
+accelerate

backend/python/bark/requirements-hipblas.txt

@@ -0,0 +1,5 @@
+--extra-index-url https://download.pytorch.org/whl/rocm6.0
+torch==2.4.1+rocm6.0
+torchaudio==2.4.1+rocm6.0
+transformers
+accelerate

backend/python/bark/requirements-intel.txt

@@ -0,0 +1,9 @@
+--extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
+intel-extension-for-pytorch==2.8.10+xpu
+torch==2.3.1+cxx11.abi
+torchaudio==2.3.1+cxx11.abi
+oneccl_bind_pt==2.3.100+xpu
+optimum[openvino]
+setuptools
+transformers
+accelerate

backend/python/bark/requirements.txt

@@ -0,0 +1,4 @@
+bark==0.1.5
+grpcio==1.74.0
+protobuf
+certifi

backend/python/bark/test.py

@@ -19,7 +19,7 @@ class TestBackendServicer(unittest.TestCase):
         This method sets up the gRPC service by starting the server
         """
         self.service = subprocess.Popen(["python3", "backend.py", "--addr", "localhost:50051"])
-        time.sleep(30)
+        time.sleep(10)
 
     def tearDown(self) -> None:
         """
@@ -52,8 +52,7 @@ class TestBackendServicer(unittest.TestCase):
             self.setUp()
             with grpc.insecure_channel("localhost:50051") as channel:
                 stub = backend_pb2_grpc.BackendStub(channel)
-                response = stub.LoadModel(backend_pb2.ModelOptions())
-                print(response)
+                response = stub.LoadModel(backend_pb2.ModelOptions(Model="v2/en_speaker_4"))
                 self.assertTrue(response.success)
                 self.assertEqual(response.message, "Model loaded successfully")
         except Exception as err:
@@ -70,7 +69,7 @@ class TestBackendServicer(unittest.TestCase):
             self.setUp()
             with grpc.insecure_channel("localhost:50051") as channel:
                 stub = backend_pb2_grpc.BackendStub(channel)
-                response = stub.LoadModel(backend_pb2.ModelOptions())
+                response = stub.LoadModel(backend_pb2.ModelOptions(Model="v2/en_speaker_4"))
                 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)

backend/python/chatterbox/backend.py

@@ -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
@@ -14,98 +14,15 @@ import backend_pb2_grpc
 import torch
 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."""
-    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
-
-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):
@@ -130,28 +47,6 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
         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 = {}
-
-        # 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
-
         self.AudioPath = None
 
         if os.path.isabs(request.AudioPath):
@@ -161,14 +56,10 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
             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)
-            if "multilingual" in self.options:
-                # remove key from options
-                del self.options["multilingual"]
-                self.model = ChatterboxMultilingualTTS.from_pretrained(device=device)
-            else:
-                self.model = ChatterboxTTS.from_pretrained(device=device)
+            self.model = ChatterboxTTS.from_pretrained(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
@@ -177,43 +68,14 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
 
     def TTS(self, request, context):
         try:
-            kwargs = {}
-
-            if "language" in self.options:
-                kwargs["language_id"] = self.options["language"]
+            # Generate audio using ChatterboxTTS
             if self.AudioPath is not None:
-                kwargs["audio_prompt_path"] = self.AudioPath
-
-            # 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)
+                wav = self.model.generate(request.text, audio_prompt_path=self.AudioPath)
             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)
+                wav = self.model.generate(request.text)
+            
+            # 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)=}")

backend/python/chatterbox/install.sh

@@ -15,11 +15,5 @@ fi
 if [ "x${BUILD_PROFILE}" == "xintel" ]; then
     EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
 fi
-EXTRA_PIP_INSTALL_FLAGS+=" --no-build-isolation"
-
-if [ "x${BUILD_PROFILE}" == "xl4t12" ]; then
-    USE_PIP=true
-fi
-
 
 installRequirements

backend/python/chatterbox/requirements-cpu.txt

@@ -1,9 +1,6 @@
 --extra-index-url https://download.pytorch.org/whl/cpu
 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
-#chatterbox-tts==0.1.4
+torch==2.6.0
+torchaudio==2.6.0
+transformers==4.46.3
+chatterbox-tts==0.1.2

backend/python/chatterbox/requirements-cublas11.txt

@@ -0,0 +1,6 @@
+--extra-index-url https://download.pytorch.org/whl/cu118
+torch==2.6.0+cu118
+torchaudio==2.6.0+cu118
+transformers==4.46.3
+chatterbox-tts==0.1.2
+accelerate

backend/python/chatterbox/requirements-cublas12.txt

@@ -1,7 +1,5 @@
-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
+torch==2.6.0
+torchaudio==2.6.0
+transformers==4.46.3
+chatterbox-tts==0.1.2
 accelerate

backend/python/chatterbox/requirements-cublas13.txt

@@ -1,8 +0,0 @@
---extra-index-url https://download.pytorch.org/whl/cu130
-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

backend/python/chatterbox/requirements-hipblas.txt

@@ -1,8 +1,6 @@
---extra-index-url https://download.pytorch.org/whl/rocm6.4
-torch==2.9.1+rocm6.4
-torchaudio==2.9.1+rocm6.4
-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
+--extra-index-url https://download.pytorch.org/whl/rocm6.0
+torch==2.6.0+rocm6.1
+torchaudio==2.6.0+rocm6.1
+transformers==4.46.3
+chatterbox-tts==0.1.2
 accelerate

backend/python/chatterbox/requirements-install.txt

@@ -1,5 +0,0 @@
-# Build dependencies needed for packages installed from source (e.g., git dependencies)
-# When using --no-build-isolation, these must be installed in the venv first
-wheel
-setuptools
-packaging

backend/python/chatterbox/requirements-intel.txt

@@ -1,10 +1,9 @@
---extra-index-url https://download.pytorch.org/whl/xpu
-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
+--extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
+intel-extension-for-pytorch==2.3.110+xpu
+torch==2.3.1+cxx11.abi
+torchaudio==2.3.1+cxx11.abi
+transformers==4.46.3
+chatterbox-tts==0.1.2
 accelerate
 oneccl_bind_pt==2.3.100+xpu
 optimum[openvino]