Final: Fix complete and tested - MCP toggle now shows for all models with MCP config

Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>

.air.toml

@@ -0,0 +1,8 @@
+# .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

.dockerignore

@@ -6,6 +6,10 @@ models
 backends
 examples/chatbot-ui/models
 backend/go/image/stablediffusion-ggml/build/
+backend/go/*/build
+backend/go/*/.cache
+backend/go/*/sources
+backend/go/*/package
 examples/rwkv/models
 examples/**/models
 Dockerfile*

.github/gallery-agent/agent.go

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

.github/gallery-agent/gallery.go

@@ -0,0 +1,203 @@
+package main
+
+import (
+	"context"
+	"fmt"
+	"os"
+	"strings"
+)
+
+// generateYAMLEntry generates a YAML entry for a model using the specified anchor
+func generateYAMLEntry(model ProcessedModel, familyAnchor string) string {
+	// Extract model name from ModelID
+	parts := strings.Split(model.ModelID, "/")
+	modelName := model.ModelID
+	if len(parts) > 0 {
+		modelName = strings.ToLower(parts[len(parts)-1])
+	}
+	// Remove common suffixes
+	modelName = strings.ReplaceAll(modelName, "-gguf", "")
+	modelName = strings.ReplaceAll(modelName, "-q4_k_m", "")
+	modelName = strings.ReplaceAll(modelName, "-q4_k_s", "")
+	modelName = strings.ReplaceAll(modelName, "-q3_k_m", "")
+	modelName = strings.ReplaceAll(modelName, "-q2_k", "")
+
+	fileName := ""
+	checksum := ""
+	if model.PreferredModelFile != nil {
+		fileParts := strings.Split(model.PreferredModelFile.Path, "/")
+		if len(fileParts) > 0 {
+			fileName = fileParts[len(fileParts)-1]
+		}
+		checksum = model.PreferredModelFile.SHA256
+	} else {
+		fileName = model.ModelID
+	}
+
+	description := model.ReadmeContent
+	if description == "" {
+		description = fmt.Sprintf("AI model: %s", modelName)
+	}
+
+	// Clean up description to prevent YAML linting issues
+	description = cleanTextContent(description)
+
+	// Format description for YAML (indent each line and ensure no trailing spaces)
+	lines := strings.Split(description, "\n")
+	var formattedLines []string
+	for _, line := range lines {
+		if strings.TrimSpace(line) == "" {
+			// Keep empty lines as empty (no indentation)
+			formattedLines = append(formattedLines, "")
+		} else {
+			// Add indentation to non-empty lines
+			formattedLines = append(formattedLines, "    "+line)
+		}
+	}
+	formattedDescription := strings.Join(formattedLines, "\n")
+	// Remove any trailing spaces from the formatted description
+	formattedDescription = strings.TrimRight(formattedDescription, " \t")
+	yamlTemplate := ""
+	if checksum != "" {
+		yamlTemplate = `- !!merge <<: *%s
+  name: "%s"
+  urls:
+    - https://huggingface.co/%s
+  description: |
+%s
+  overrides:
+    parameters:
+      model: %s
+  files:
+    - filename: %s
+      sha256: %s
+      uri: huggingface://%s/%s`
+		return fmt.Sprintf(yamlTemplate,
+			familyAnchor,
+			modelName,
+			model.ModelID,
+			formattedDescription,
+			fileName,
+			fileName,
+			checksum,
+			model.ModelID,
+			fileName,
+		)
+	} else {
+		yamlTemplate = `- !!merge <<: *%s
+  name: "%s"
+  urls:
+    - https://huggingface.co/%s
+  description: |
+%s
+  overrides:
+    parameters:
+      model: %s`
+		return fmt.Sprintf(yamlTemplate,
+			familyAnchor,
+			modelName,
+			model.ModelID,
+			formattedDescription,
+			fileName,
+		)
+	}
+}
+
+// extractModelFamilies extracts all YAML anchors from the gallery index.yaml file
+func extractModelFamilies() ([]ModelFamily, error) {
+	// Read the index.yaml file
+	indexPath := getGalleryIndexPath()
+	content, err := os.ReadFile(indexPath)
+	if err != nil {
+		return nil, fmt.Errorf("failed to read %s: %w", indexPath, err)
+	}
+
+	lines := strings.Split(string(content), "\n")
+	var families []ModelFamily
+
+	for _, line := range lines {
+		line = strings.TrimSpace(line)
+		// Look for YAML anchors (lines starting with "- &")
+		if strings.HasPrefix(line, "- &") {
+			// Extract the anchor name (everything after "- &")
+			anchor := strings.TrimPrefix(line, "- &")
+			// Remove any trailing colon or other characters
+			anchor = strings.Split(anchor, ":")[0]
+			anchor = strings.Split(anchor, " ")[0]
+
+			if anchor != "" {
+				families = append(families, ModelFamily{
+					Anchor: anchor,
+					Name:   anchor, // Use anchor as name for now
+				})
+			}
+		}
+	}
+
+	return families, nil
+}
+
+// generateYAMLForModels generates YAML entries for selected models and appends to index.yaml
+func generateYAMLForModels(ctx context.Context, models []ProcessedModel) error {
+	// Extract available model families
+	families, err := extractModelFamilies()
+	if err != nil {
+		return fmt.Errorf("failed to extract model families: %w", err)
+	}
+
+	fmt.Printf("Found %d model families: %v\n", len(families),
+		func() []string {
+			var names []string
+			for _, f := range families {
+				names = append(names, f.Anchor)
+			}
+			return names
+		}())
+
+	// Generate YAML entries for each model
+	var yamlEntries []string
+	for _, model := range models {
+		fmt.Printf("Selecting family for model: %s\n", model.ModelID)
+
+		// Select appropriate family for this model
+		familyAnchor, err := selectModelFamily(ctx, model, families)
+		if err != nil {
+			fmt.Printf("Error selecting family for %s: %v, using default\n", model.ModelID, err)
+			familyAnchor = "llama3" // Default fallback
+		}
+
+		fmt.Printf("Selected family '%s' for model %s\n", familyAnchor, model.ModelID)
+
+		// Generate YAML entry
+		yamlEntry := generateYAMLEntry(model, familyAnchor)
+		yamlEntries = append(yamlEntries, yamlEntry)
+	}
+
+	// Append to index.yaml
+	if len(yamlEntries) > 0 {
+		indexPath := getGalleryIndexPath()
+		fmt.Printf("Appending YAML entries to %s...\n", indexPath)
+
+		// Read current content
+		content, err := os.ReadFile(indexPath)
+		if err != nil {
+			return fmt.Errorf("failed to read %s: %w", indexPath, err)
+		}
+
+		// Append new entries
+		// Remove trailing whitespace from existing content and join entries without extra newlines
+		existingContent := strings.TrimRight(string(content), " \t\n\r")
+		yamlBlock := strings.Join(yamlEntries, "\n")
+		newContent := existingContent + "\n" + yamlBlock + "\n"
+
+		// Write back to file
+		err = os.WriteFile(indexPath, []byte(newContent), 0644)
+		if err != nil {
+			return fmt.Errorf("failed to write %s: %w", indexPath, err)
+		}
+
+		fmt.Printf("Successfully added %d models to %s\n", len(yamlEntries), indexPath)
+	}
+
+	return nil
+}

.github/gallery-agent/main.go

@@ -0,0 +1,351 @@
+package main
+
+import (
+	"context"
+	"encoding/json"
+	"fmt"
+	"os"
+	"strconv"
+	"strings"
+	"time"
+
+	hfapi "github.com/mudler/LocalAI/pkg/huggingface-api"
+)
+
+// ProcessedModelFile represents a processed model file with additional metadata
+type ProcessedModelFile struct {
+	Path     string `json:"path"`
+	Size     int64  `json:"size"`
+	SHA256   string `json:"sha256"`
+	IsReadme bool   `json:"is_readme"`
+	FileType string `json:"file_type"` // "model", "readme", "other"
+}
+
+// ProcessedModel represents a processed model with all gathered metadata
+type ProcessedModel struct {
+	ModelID                 string               `json:"model_id"`
+	Author                  string               `json:"author"`
+	Downloads               int                  `json:"downloads"`
+	LastModified            string               `json:"last_modified"`
+	Files                   []ProcessedModelFile `json:"files"`
+	PreferredModelFile      *ProcessedModelFile  `json:"preferred_model_file,omitempty"`
+	ReadmeFile              *ProcessedModelFile  `json:"readme_file,omitempty"`
+	ReadmeContent           string               `json:"readme_content,omitempty"`
+	ReadmeContentPreview    string               `json:"readme_content_preview,omitempty"`
+	QuantizationPreferences []string             `json:"quantization_preferences"`
+	ProcessingError         string               `json:"processing_error,omitempty"`
+}
+
+// SearchResult represents the complete result of searching and processing models
+type SearchResult struct {
+	SearchTerm       string           `json:"search_term"`
+	Limit            int              `json:"limit"`
+	Quantization     string           `json:"quantization"`
+	TotalModelsFound int              `json:"total_models_found"`
+	Models           []ProcessedModel `json:"models"`
+	FormattedOutput  string           `json:"formatted_output"`
+}
+
+// AddedModelSummary represents a summary of models added to the gallery
+type AddedModelSummary struct {
+	SearchTerm     string   `json:"search_term"`
+	TotalFound     int      `json:"total_found"`
+	ModelsAdded    int      `json:"models_added"`
+	AddedModelIDs  []string `json:"added_model_ids"`
+	AddedModelURLs []string `json:"added_model_urls"`
+	Quantization   string   `json:"quantization"`
+	ProcessingTime string   `json:"processing_time"`
+}
+
+func main() {
+	startTime := time.Now()
+
+	// Check for synthetic mode
+	syntheticMode := os.Getenv("SYNTHETIC_MODE")
+	if syntheticMode == "true" || syntheticMode == "1" {
+		fmt.Println("Running in SYNTHETIC MODE - generating random test data")
+		err := runSyntheticMode()
+		if err != nil {
+			fmt.Fprintf(os.Stderr, "Error in synthetic mode: %v\n", err)
+			os.Exit(1)
+		}
+		return
+	}
+
+	// Get configuration from environment variables
+	searchTerm := os.Getenv("SEARCH_TERM")
+	if searchTerm == "" {
+		searchTerm = "GGUF"
+	}
+
+	limitStr := os.Getenv("LIMIT")
+	if limitStr == "" {
+		limitStr = "5"
+	}
+	limit, err := strconv.Atoi(limitStr)
+	if err != nil {
+		fmt.Fprintf(os.Stderr, "Error parsing LIMIT: %v\n", err)
+		os.Exit(1)
+	}
+
+	quantization := os.Getenv("QUANTIZATION")
+
+	maxModels := os.Getenv("MAX_MODELS")
+	if maxModels == "" {
+		maxModels = "1"
+	}
+	maxModelsInt, err := strconv.Atoi(maxModels)
+	if err != nil {
+		fmt.Fprintf(os.Stderr, "Error parsing MAX_MODELS: %v\n", err)
+		os.Exit(1)
+	}
+
+	// Print configuration
+	fmt.Printf("Gallery Agent Configuration:\n")
+	fmt.Printf("  Search Term: %s\n", searchTerm)
+	fmt.Printf("  Limit: %d\n", limit)
+	fmt.Printf("  Quantization: %s\n", quantization)
+	fmt.Printf("  Max Models to Add: %d\n", maxModelsInt)
+	fmt.Printf("  Gallery Index Path: %s\n", os.Getenv("GALLERY_INDEX_PATH"))
+	fmt.Println()
+
+	result, err := searchAndProcessModels(searchTerm, limit, quantization)
+	if err != nil {
+		fmt.Fprintf(os.Stderr, "Error: %v\n", err)
+		os.Exit(1)
+	}
+
+	fmt.Println(result.FormattedOutput)
+
+	// Use AI agent to select the most interesting models
+	fmt.Println("Using AI agent to select the most interesting models...")
+	models, err := selectMostInterestingModels(context.Background(), result)
+	if err != nil {
+		fmt.Fprintf(os.Stderr, "Error in model selection: %v\n", err)
+		// Continue with original result if selection fails
+		models = result.Models
+	}
+
+	fmt.Print(models)
+
+	// Filter out models that already exist in the gallery
+	fmt.Println("Filtering out existing models...")
+	models, err = filterExistingModels(models)
+	if err != nil {
+		fmt.Fprintf(os.Stderr, "Error filtering existing models: %v\n", err)
+		os.Exit(1)
+	}
+
+	// Limit to maxModelsInt after filtering
+	if len(models) > maxModelsInt {
+		models = models[:maxModelsInt]
+	}
+
+	// Track added models for summary
+	var addedModelIDs []string
+	var addedModelURLs []string
+
+	// Generate YAML entries and append to gallery/index.yaml
+	if len(models) > 0 {
+		for _, model := range models {
+			addedModelIDs = append(addedModelIDs, model.ModelID)
+			// Generate Hugging Face URL for the model
+			modelURL := fmt.Sprintf("https://huggingface.co/%s", model.ModelID)
+			addedModelURLs = append(addedModelURLs, modelURL)
+		}
+		fmt.Println("Generating YAML entries for selected models...")
+		err = generateYAMLForModels(context.Background(), models)
+		if err != nil {
+			fmt.Fprintf(os.Stderr, "Error generating YAML entries: %v\n", err)
+			os.Exit(1)
+		}
+	} else {
+		fmt.Println("No new models to add to the gallery.")
+	}
+
+	// Create and write summary
+	processingTime := time.Since(startTime).String()
+	summary := AddedModelSummary{
+		SearchTerm:     searchTerm,
+		TotalFound:     result.TotalModelsFound,
+		ModelsAdded:    len(addedModelIDs),
+		AddedModelIDs:  addedModelIDs,
+		AddedModelURLs: addedModelURLs,
+		Quantization:   quantization,
+		ProcessingTime: processingTime,
+	}
+
+	// Write summary to file
+	summaryData, err := json.MarshalIndent(summary, "", "  ")
+	if err != nil {
+		fmt.Fprintf(os.Stderr, "Error marshaling summary: %v\n", err)
+	} else {
+		err = os.WriteFile("gallery-agent-summary.json", summaryData, 0644)
+		if err != nil {
+			fmt.Fprintf(os.Stderr, "Error writing summary file: %v\n", err)
+		} else {
+			fmt.Printf("Summary written to gallery-agent-summary.json\n")
+		}
+	}
+}
+
+func searchAndProcessModels(searchTerm string, limit int, quantization string) (*SearchResult, error) {
+	client := hfapi.NewClient()
+	var outputBuilder strings.Builder
+
+	fmt.Println("Searching for models...")
+	// Initialize the result struct
+	result := &SearchResult{
+		SearchTerm:   searchTerm,
+		Limit:        limit,
+		Quantization: quantization,
+		Models:       []ProcessedModel{},
+	}
+
+	models, err := client.GetLatest(searchTerm, limit)
+	if err != nil {
+		return nil, fmt.Errorf("failed to fetch models: %w", err)
+	}
+
+	fmt.Println("Models found:", len(models))
+	result.TotalModelsFound = len(models)
+
+	if len(models) == 0 {
+		outputBuilder.WriteString("No models found.\n")
+		result.FormattedOutput = outputBuilder.String()
+		return result, nil
+	}
+
+	outputBuilder.WriteString(fmt.Sprintf("Found %d models matching '%s':\n\n", len(models), searchTerm))
+
+	// Process each model
+	for i, model := range models {
+		outputBuilder.WriteString(fmt.Sprintf("%d. Processing Model: %s\n", i+1, model.ModelID))
+		outputBuilder.WriteString(fmt.Sprintf("   Author: %s\n", model.Author))
+		outputBuilder.WriteString(fmt.Sprintf("   Downloads: %d\n", model.Downloads))
+		outputBuilder.WriteString(fmt.Sprintf("   Last Modified: %s\n", model.LastModified))
+
+		// Initialize processed model struct
+		processedModel := ProcessedModel{
+			ModelID:                 model.ModelID,
+			Author:                  model.Author,
+			Downloads:               model.Downloads,
+			LastModified:            model.LastModified,
+			QuantizationPreferences: []string{quantization, "Q4_K_M", "Q4_K_S", "Q3_K_M", "Q2_K"},
+		}
+
+		// Get detailed model information
+		details, err := client.GetModelDetails(model.ModelID)
+		if err != nil {
+			errorMsg := fmt.Sprintf("   Error getting model details: %v\n", err)
+			outputBuilder.WriteString(errorMsg)
+			processedModel.ProcessingError = err.Error()
+			result.Models = append(result.Models, processedModel)
+			continue
+		}
+
+		// Define quantization preferences (in order of preference)
+		quantizationPreferences := []string{quantization, "Q4_K_M", "Q4_K_S", "Q3_K_M", "Q2_K"}
+
+		// Find preferred model file
+		preferredModelFile := hfapi.FindPreferredModelFile(details.Files, quantizationPreferences)
+
+		// Process files
+		processedFiles := make([]ProcessedModelFile, len(details.Files))
+		for j, file := range details.Files {
+			fileType := "other"
+			if file.IsReadme {
+				fileType = "readme"
+			} else if preferredModelFile != nil && file.Path == preferredModelFile.Path {
+				fileType = "model"
+			}
+
+			processedFiles[j] = ProcessedModelFile{
+				Path:     file.Path,
+				Size:     file.Size,
+				SHA256:   file.SHA256,
+				IsReadme: file.IsReadme,
+				FileType: fileType,
+			}
+		}
+
+		processedModel.Files = processedFiles
+
+		// Set preferred model file
+		if preferredModelFile != nil {
+			for _, file := range processedFiles {
+				if file.Path == preferredModelFile.Path {
+					processedModel.PreferredModelFile = &file
+					break
+				}
+			}
+		}
+
+		// Print file information
+		outputBuilder.WriteString(fmt.Sprintf("   Files found: %d\n", len(details.Files)))
+
+		if preferredModelFile != nil {
+			outputBuilder.WriteString(fmt.Sprintf("   Preferred Model File: %s (SHA256: %s)\n",
+				preferredModelFile.Path,
+				preferredModelFile.SHA256))
+		} else {
+			outputBuilder.WriteString(fmt.Sprintf("   No model file found with quantization preferences: %v\n", quantizationPreferences))
+		}
+
+		if details.ReadmeFile != nil {
+			outputBuilder.WriteString(fmt.Sprintf("   README File: %s\n", details.ReadmeFile.Path))
+
+			// Find and set readme file
+			for _, file := range processedFiles {
+				if file.IsReadme {
+					processedModel.ReadmeFile = &file
+					break
+				}
+			}
+
+			fmt.Println("Getting real readme for", model.ModelID, "waiting...")
+			// Use agent to get the real readme and prepare the model description
+			readmeContent, err := getRealReadme(context.Background(), model.ModelID)
+			if err == nil {
+				processedModel.ReadmeContent = readmeContent
+				processedModel.ReadmeContentPreview = truncateString(readmeContent, 200)
+				outputBuilder.WriteString(fmt.Sprintf("   README Content Preview: %s\n",
+					processedModel.ReadmeContentPreview))
+			} else {
+				continue
+			}
+			fmt.Println("Real readme got", readmeContent)
+			// Get README content
+			// readmeContent, err := client.GetReadmeContent(model.ModelID, details.ReadmeFile.Path)
+			// if err == nil {
+			// 	processedModel.ReadmeContent = readmeContent
+			// 	processedModel.ReadmeContentPreview = truncateString(readmeContent, 200)
+			// 	outputBuilder.WriteString(fmt.Sprintf("   README Content Preview: %s\n",
+			// 		processedModel.ReadmeContentPreview))
+			// }
+		}
+
+		// Print all files with their checksums
+		outputBuilder.WriteString("   All Files:\n")
+		for _, file := range processedFiles {
+			outputBuilder.WriteString(fmt.Sprintf("     - %s (%s, %d bytes", file.Path, file.FileType, file.Size))
+			if file.SHA256 != "" {
+				outputBuilder.WriteString(fmt.Sprintf(", SHA256: %s", file.SHA256))
+			}
+			outputBuilder.WriteString(")\n")
+		}
+
+		outputBuilder.WriteString("\n")
+		result.Models = append(result.Models, processedModel)
+	}
+
+	result.FormattedOutput = outputBuilder.String()
+	return result, nil
+}
+
+func truncateString(s string, maxLen int) string {
+	if len(s) <= maxLen {
+		return s
+	}
+	return s[:maxLen] + "..."
+}

.github/gallery-agent/testing.go

@@ -0,0 +1,190 @@
+package main
+
+import (
+	"context"
+	"fmt"
+	"math/rand"
+	"strings"
+	"time"
+)
+
+// runSyntheticMode generates synthetic test data and appends it to the gallery
+func runSyntheticMode() error {
+	generator := NewSyntheticDataGenerator()
+
+	// Generate a random number of synthetic models (1-3)
+	numModels := generator.rand.Intn(3) + 1
+	fmt.Printf("Generating %d synthetic models for testing...\n", numModels)
+
+	var models []ProcessedModel
+	for i := 0; i < numModels; i++ {
+		model := generator.GenerateProcessedModel()
+		models = append(models, model)
+		fmt.Printf("Generated synthetic model: %s\n", model.ModelID)
+	}
+
+	// Generate YAML entries and append to gallery/index.yaml
+	fmt.Println("Generating YAML entries for synthetic models...")
+	err := generateYAMLForModels(context.Background(), models)
+	if err != nil {
+		return fmt.Errorf("error generating YAML entries: %w", err)
+	}
+
+	fmt.Printf("Successfully added %d synthetic models to the gallery for testing!\n", len(models))
+	return nil
+}
+
+// SyntheticDataGenerator provides methods to generate synthetic test data
+type SyntheticDataGenerator struct {
+	rand *rand.Rand
+}
+
+// NewSyntheticDataGenerator creates a new synthetic data generator
+func NewSyntheticDataGenerator() *SyntheticDataGenerator {
+	return &SyntheticDataGenerator{
+		rand: rand.New(rand.NewSource(time.Now().UnixNano())),
+	}
+}
+
+// GenerateProcessedModelFile creates a synthetic ProcessedModelFile
+func (g *SyntheticDataGenerator) GenerateProcessedModelFile() ProcessedModelFile {
+	fileTypes := []string{"model", "readme", "other"}
+	fileType := fileTypes[g.rand.Intn(len(fileTypes))]
+
+	var path string
+	var isReadme bool
+
+	switch fileType {
+	case "model":
+		path = fmt.Sprintf("model-%s.gguf", g.randomString(8))
+		isReadme = false
+	case "readme":
+		path = "README.md"
+		isReadme = true
+	default:
+		path = fmt.Sprintf("file-%s.txt", g.randomString(6))
+		isReadme = false
+	}
+
+	return ProcessedModelFile{
+		Path:     path,
+		Size:     int64(g.rand.Intn(1000000000) + 1000000), // 1MB to 1GB
+		SHA256:   g.randomSHA256(),
+		IsReadme: isReadme,
+		FileType: fileType,
+	}
+}
+
+// GenerateProcessedModel creates a synthetic ProcessedModel
+func (g *SyntheticDataGenerator) GenerateProcessedModel() ProcessedModel {
+	authors := []string{"microsoft", "meta", "google", "openai", "anthropic", "mistralai", "huggingface"}
+	modelNames := []string{"llama", "gpt", "claude", "mistral", "gemma", "phi", "qwen", "codellama"}
+
+	author := authors[g.rand.Intn(len(authors))]
+	modelName := modelNames[g.rand.Intn(len(modelNames))]
+	modelID := fmt.Sprintf("%s/%s-%s", author, modelName, g.randomString(6))
+
+	// Generate files
+	numFiles := g.rand.Intn(5) + 2 // 2-6 files
+	files := make([]ProcessedModelFile, numFiles)
+
+	// Ensure at least one model file and one readme
+	hasModelFile := false
+	hasReadme := false
+
+	for i := 0; i < numFiles; i++ {
+		files[i] = g.GenerateProcessedModelFile()
+		if files[i].FileType == "model" {
+			hasModelFile = true
+		}
+		if files[i].FileType == "readme" {
+			hasReadme = true
+		}
+	}
+
+	// Add required files if missing
+	if !hasModelFile {
+		modelFile := g.GenerateProcessedModelFile()
+		modelFile.FileType = "model"
+		modelFile.Path = fmt.Sprintf("%s-Q4_K_M.gguf", modelName)
+		files = append(files, modelFile)
+	}
+
+	if !hasReadme {
+		readmeFile := g.GenerateProcessedModelFile()
+		readmeFile.FileType = "readme"
+		readmeFile.Path = "README.md"
+		readmeFile.IsReadme = true
+		files = append(files, readmeFile)
+	}
+
+	// Find preferred model file
+	var preferredModelFile *ProcessedModelFile
+	for i := range files {
+		if files[i].FileType == "model" {
+			preferredModelFile = &files[i]
+			break
+		}
+	}
+
+	// Find readme file
+	var readmeFile *ProcessedModelFile
+	for i := range files {
+		if files[i].FileType == "readme" {
+			readmeFile = &files[i]
+			break
+		}
+	}
+
+	readmeContent := g.generateReadmeContent(modelName, author)
+
+	return ProcessedModel{
+		ModelID:                 modelID,
+		Author:                  author,
+		Downloads:               g.rand.Intn(1000000) + 1000,
+		LastModified:            g.randomDate(),
+		Files:                   files,
+		PreferredModelFile:      preferredModelFile,
+		ReadmeFile:              readmeFile,
+		ReadmeContent:           readmeContent,
+		ReadmeContentPreview:    truncateString(readmeContent, 200),
+		QuantizationPreferences: []string{"Q4_K_M", "Q4_K_S", "Q3_K_M", "Q2_K"},
+		ProcessingError:         "",
+	}
+}
+
+// Helper methods for synthetic data generation
+func (g *SyntheticDataGenerator) randomString(length int) string {
+	const charset = "abcdefghijklmnopqrstuvwxyz0123456789"
+	b := make([]byte, length)
+	for i := range b {
+		b[i] = charset[g.rand.Intn(len(charset))]
+	}
+	return string(b)
+}
+
+func (g *SyntheticDataGenerator) randomSHA256() string {
+	const charset = "0123456789abcdef"
+	b := make([]byte, 64)
+	for i := range b {
+		b[i] = charset[g.rand.Intn(len(charset))]
+	}
+	return string(b)
+}
+
+func (g *SyntheticDataGenerator) randomDate() string {
+	now := time.Now()
+	daysAgo := g.rand.Intn(365) // Random date within last year
+	pastDate := now.AddDate(0, 0, -daysAgo)
+	return pastDate.Format("2006-01-02T15:04:05.000Z")
+}
+
+func (g *SyntheticDataGenerator) generateReadmeContent(modelName, author string) string {
+	templates := []string{
+		fmt.Sprintf("# %s Model\n\nThis is a %s model developed by %s. It's designed for various natural language processing tasks including text generation, question answering, and conversation.\n\n## Features\n\n- High-quality text generation\n- Efficient inference\n- Multiple quantization options\n- Easy to use with LocalAI\n\n## Usage\n\nUse this model with LocalAI for various AI tasks.", strings.Title(modelName), modelName, author),
+		fmt.Sprintf("# %s\n\nA powerful language model from %s. This model excels at understanding and generating human-like text across multiple domains.\n\n## Capabilities\n\n- Text completion\n- Code generation\n- Creative writing\n- Technical documentation\n\n## Model Details\n\n- Architecture: Transformer-based\n- Training: Large-scale supervised learning\n- Quantization: Available in multiple formats", strings.Title(modelName), author),
+		fmt.Sprintf("# %s Language Model\n\nDeveloped by %s, this model represents state-of-the-art performance in natural language understanding and generation.\n\n## Key Features\n\n- Multilingual support\n- Context-aware responses\n- Efficient memory usage\n- Fast inference speed\n\n## Applications\n\n- Chatbots and virtual assistants\n- Content generation\n- Code completion\n- Educational tools", strings.Title(modelName), author),
+	}
+
+	return templates[g.rand.Intn(len(templates))]
+}

.github/gallery-agent/tools.go

@@ -0,0 +1,46 @@
+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.yml

@@ -87,6 +87,42 @@ jobs:
             backend: "diffusers"
             dockerfile: "./backend/Dockerfile.python"
             context: "./backend"
+          - build-type: 'l4t'
+            cuda-major-version: "12"
+            cuda-minor-version: "0"
+            platforms: 'linux/arm64'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-nvidia-l4t-diffusers'
+            runs-on: 'ubuntu-24.04-arm'
+            base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
+            skip-drivers: 'true'
+            backend: "diffusers"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./backend"
+          - build-type: ''
+            cuda-major-version: ""
+            cuda-minor-version: ""
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-cpu-diffusers'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
+            skip-drivers: 'true'
+            backend: "diffusers"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./backend"
+          - build-type: ''
+            cuda-major-version: ""
+            cuda-minor-version: ""
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-cpu-chatterbox'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
+            skip-drivers: 'true'
+            backend: "chatterbox"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./backend"
           # CUDA 11 additional backends
           - build-type: 'cublas'
             cuda-major-version: "11"
@@ -179,7 +215,7 @@ jobs:
             platforms: 'linux/amd64'
             tag-latest: 'auto'
             tag-suffix: '-gpu-nvidia-cuda-12-vllm'
-            runs-on: 'ubuntu-latest'
+            runs-on: 'arc-runner-set'
             base-image: "ubuntu:22.04"
             skip-drivers: 'false'
             backend: "vllm"
@@ -206,7 +242,7 @@ jobs:
             runs-on: 'ubuntu-latest'
             base-image: "ubuntu:22.04"
             skip-drivers: 'false'
-            backend: "diffusers"            
+            backend: "diffusers"
             dockerfile: "./backend/Dockerfile.python"
             context: "./backend"
           # CUDA 12 additional backends
@@ -278,7 +314,7 @@ jobs:
             tag-latest: 'auto'
             tag-suffix: '-gpu-rocm-hipblas-rerankers'
             runs-on: 'ubuntu-latest'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
             skip-drivers: 'false'
             backend: "rerankers"
             dockerfile: "./backend/Dockerfile.python"
@@ -290,7 +326,7 @@ jobs:
             tag-latest: 'auto'
             tag-suffix: '-gpu-rocm-hipblas-llama-cpp'
             runs-on: 'ubuntu-latest'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
             skip-drivers: 'false'
             backend: "llama-cpp"
             dockerfile: "./backend/Dockerfile.llama-cpp"
@@ -301,8 +337,8 @@ jobs:
             platforms: 'linux/amd64'
             tag-latest: 'auto'
             tag-suffix: '-gpu-rocm-hipblas-vllm'
-            runs-on: 'ubuntu-latest'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            runs-on: 'arc-runner-set'
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
             skip-drivers: 'false'
             backend: "vllm"
             dockerfile: "./backend/Dockerfile.python"
@@ -313,8 +349,8 @@ jobs:
             platforms: 'linux/amd64'
             tag-latest: 'auto'
             tag-suffix: '-gpu-rocm-hipblas-transformers'
-            runs-on: 'ubuntu-latest'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            runs-on: 'arc-runner-set'
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
             skip-drivers: 'false'
             backend: "transformers"
             dockerfile: "./backend/Dockerfile.python"
@@ -325,8 +361,8 @@ jobs:
             platforms: 'linux/amd64'
             tag-latest: 'auto'
             tag-suffix: '-gpu-rocm-hipblas-diffusers'
-            runs-on: 'ubuntu-latest'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            runs-on: 'arc-runner-set'
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
             skip-drivers: 'false'
             backend: "diffusers"
             dockerfile: "./backend/Dockerfile.python"
@@ -338,8 +374,8 @@ jobs:
             platforms: 'linux/amd64'
             tag-latest: 'auto'
             tag-suffix: '-gpu-rocm-hipblas-kokoro'
-            runs-on: 'ubuntu-latest'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            runs-on: 'arc-runner-set'
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
             skip-drivers: 'false'
             backend: "kokoro"
             dockerfile: "./backend/Dockerfile.python"
@@ -351,7 +387,7 @@ jobs:
             tag-latest: 'auto'
             tag-suffix: '-gpu-rocm-hipblas-faster-whisper'
             runs-on: 'ubuntu-latest'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
             skip-drivers: 'false'
             backend: "faster-whisper"
             dockerfile: "./backend/Dockerfile.python"
@@ -363,7 +399,7 @@ jobs:
             tag-latest: 'auto'
             tag-suffix: '-gpu-rocm-hipblas-coqui'
             runs-on: 'ubuntu-latest'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
             skip-drivers: 'false'
             backend: "coqui"
             dockerfile: "./backend/Dockerfile.python"
@@ -374,8 +410,8 @@ jobs:
             platforms: 'linux/amd64'
             tag-latest: 'auto'
             tag-suffix: '-gpu-rocm-hipblas-bark'
-            runs-on: 'ubuntu-latest'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            runs-on: 'arc-runner-set'
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
             skip-drivers: 'false'
             backend: "bark"
             dockerfile: "./backend/Dockerfile.python"
@@ -423,7 +459,7 @@ jobs:
             platforms: 'linux/amd64'
             tag-latest: 'auto'
             tag-suffix: '-gpu-intel-vllm'
-            runs-on: 'ubuntu-latest'
+            runs-on: 'arc-runner-set'
             base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
             skip-drivers: 'false'
             backend: "vllm"
@@ -453,6 +489,18 @@ jobs:
             backend: "diffusers"
             dockerfile: "./backend/Dockerfile.python"
             context: "./backend"
+          - build-type: 'l4t'
+            cuda-major-version: "12"
+            cuda-minor-version: "0"
+            platforms: 'linux/arm64'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-nvidia-l4t-kokoro'
+            runs-on: 'ubuntu-24.04-arm'
+            base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
+            skip-drivers: 'true'
+            backend: "kokoro"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./backend"
           # SYCL additional backends
           - build-type: 'intel'
             cuda-major-version: ""
@@ -739,8 +787,8 @@ jobs:
             cuda-minor-version: ""
             platforms: 'linux/amd64'
             tag-latest: 'auto'
-            tag-suffix: '-gpu-hipblas-whisper'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            tag-suffix: '-gpu-rocm-hipblas-whisper'
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
             runs-on: 'ubuntu-latest'
             skip-drivers: 'false'
             backend: "whisper"
@@ -834,7 +882,7 @@ jobs:
             backend: "rfdetr"
             dockerfile: "./backend/Dockerfile.python"
             context: "./backend"
-          - build-type: 'cublas'
+          - build-type: 'l4t'
             cuda-major-version: "12"
             cuda-minor-version: "0"
             platforms: 'linux/arm64'
@@ -902,11 +950,23 @@ jobs:
             skip-drivers: 'true'
             tag-latest: 'auto'
             tag-suffix: '-gpu-hipblas-exllama2'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
             runs-on: 'ubuntu-latest'
             backend: "exllama2"
             dockerfile: "./backend/Dockerfile.python"
             context: "./backend"
+          - build-type: 'l4t'
+            cuda-major-version: "12"
+            cuda-minor-version: "0"
+            platforms: 'linux/arm64'
+            skip-drivers: 'true'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-nvidia-l4t-arm64-chatterbox'
+            base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
+            runs-on: 'ubuntu-24.04-arm'
+            backend: "chatterbox"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./backend"
           # runs out of space on the runner
           # - build-type: 'hipblas'
           #   cuda-major-version: ""
@@ -914,12 +974,115 @@ jobs:
           #   platforms: 'linux/amd64'
           #   tag-latest: 'auto'
           #   tag-suffix: '-gpu-hipblas-rfdetr'
-          #   base-image: "rocm/dev-ubuntu-22.04:6.1"
+          #   base-image: "rocm/dev-ubuntu-22.04:6.4.3"
           #   runs-on: 'ubuntu-latest'
           #   skip-drivers: 'false'
           #   backend: "rfdetr"
           #   dockerfile: "./backend/Dockerfile.python"
           #   context: "./backend"
+          # kitten-tts
+          - build-type: ''
+            cuda-major-version: ""
+            cuda-minor-version: ""
+            platforms: 'linux/amd64,linux/arm64'
+            tag-latest: 'auto'
+            tag-suffix: '-kitten-tts'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
+            skip-drivers: 'false'
+            backend: "kitten-tts"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./backend"
+          # neutts
+          - build-type: ''
+            cuda-major-version: ""
+            cuda-minor-version: ""
+            platforms: 'linux/amd64,linux/arm64'
+            tag-latest: 'auto'
+            tag-suffix: '-cpu-neutts'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
+            skip-drivers: 'false'
+            backend: "neutts"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./backend"
+          - build-type: 'cublas'
+            cuda-major-version: "12"
+            cuda-minor-version: "0"
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-nvidia-cuda-12-neutts'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:22.04"
+            skip-drivers: 'false'
+            backend: "neutts"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./backend"
+          - build-type: 'hipblas'
+            cuda-major-version: ""
+            cuda-minor-version: ""
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-rocm-hipblas-neutts'
+            runs-on: 'arc-runner-set'
+            base-image: "rocm/dev-ubuntu-22.04:6.4.3"
+            skip-drivers: 'false'
+            backend: "neutts"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./backend"
+          - build-type: 'l4t'
+            cuda-major-version: "12"
+            cuda-minor-version: "0"
+            platforms: 'linux/arm64'
+            skip-drivers: 'true'
+            tag-latest: 'auto'
+            tag-suffix: '-nvidia-l4t-arm64-neutts'
+            base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
+            runs-on: 'ubuntu-24.04-arm'
+            backend: "neutts"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./backend"
+  backend-jobs-darwin:
+    uses: ./.github/workflows/backend_build_darwin.yml
+    strategy:
+      matrix:
+        include:
+          - backend: "diffusers"
+            tag-suffix: "-metal-darwin-arm64-diffusers"
+            build-type: "mps"
+          - backend: "mlx"
+            tag-suffix: "-metal-darwin-arm64-mlx"
+            build-type: "mps"
+          - backend: "chatterbox"
+            tag-suffix: "-metal-darwin-arm64-chatterbox"
+            build-type: "mps"
+          - backend: "mlx-vlm"
+            tag-suffix: "-metal-darwin-arm64-mlx-vlm"
+            build-type: "mps"
+          - backend: "mlx-audio"
+            tag-suffix: "-metal-darwin-arm64-mlx-audio"
+            build-type: "mps"
+          - backend: "stablediffusion-ggml"
+            tag-suffix: "-metal-darwin-arm64-stablediffusion-ggml"
+            build-type: "metal"
+            lang: "go"
+          - backend: "whisper"
+            tag-suffix: "-metal-darwin-arm64-whisper"
+            build-type: "metal"
+            lang: "go"
+    with:
+      backend: ${{ matrix.backend }}
+      build-type: ${{ matrix.build-type }}
+      go-version: "1.24.x"
+      tag-suffix: ${{ matrix.tag-suffix }}
+      lang: ${{ matrix.lang || 'python' }}
+      use-pip: ${{ matrix.backend == 'diffusers' }}
+      runs-on: "macOS-14"
+    secrets:
+      dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
+      dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
   llama-cpp-darwin:
     runs-on: macOS-14
     strategy:
@@ -927,7 +1090,7 @@ jobs:
         go-version: ['1.21.x']
     steps:
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Setup Go ${{ matrix.go-version }}
@@ -944,21 +1107,19 @@ jobs:
       - name: Build llama-cpp-darwin
         run: |
           make protogen-go
-          make build
-          bash scripts/build-llama-cpp-darwin.sh
-          ls -la build/darwin.tar
-          mv build/darwin.tar build/llama-cpp.tar
+          make backends/llama-cpp-darwin
       - name: Upload llama-cpp.tar
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v5
         with:
           name: llama-cpp-tar
-          path: build/llama-cpp.tar
+          path: backend-images/llama-cpp.tar
   llama-cpp-darwin-publish:
     needs: llama-cpp-darwin
+    if: github.event_name != 'pull_request'
     runs-on: ubuntu-latest
     steps:
       - name: Download llama-cpp.tar
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v6
         with:
           name: llama-cpp-tar
           path: .
@@ -1015,7 +1176,7 @@ jobs:
         go-version: ['1.21.x']
     steps:
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Setup Go ${{ matrix.go-version }}
@@ -1034,20 +1195,19 @@ jobs:
           make protogen-go
           make build
           export PLATFORMARCH=darwin/amd64
-          bash scripts/build-llama-cpp-darwin.sh
-          ls -la build/darwin.tar
-          mv build/darwin.tar build/llama-cpp.tar
+          make backends/llama-cpp-darwin
       - name: Upload llama-cpp.tar
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v5
         with:
           name: llama-cpp-tar-x86
-          path: build/llama-cpp.tar
+          path: backend-images/llama-cpp.tar
   llama-cpp-darwin-x86-publish:
+    if: github.event_name != 'pull_request'
     needs: llama-cpp-darwin-x86
     runs-on: ubuntu-latest
     steps:
       - name: Download llama-cpp.tar
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v6
         with:
           name: llama-cpp-tar-x86
           path: .
@@ -1096,4 +1256,4 @@ jobs:
         run: |
           for tag in $(echo "${{ steps.quaymeta.outputs.tags }}" | tr ',' '\n'); do
             crane push llama-cpp.tar $tag
-          done
+          done

.github/workflows/backend_build.yml

@@ -55,9 +55,9 @@ on:
         type: string
     secrets:
       dockerUsername:
-        required: true
+        required: false
       dockerPassword:
-        required: true
+        required: false
       quayUsername:
         required: true
       quayPassword:
@@ -66,6 +66,8 @@ on:
 jobs:
   backend-build:
     runs-on: ${{ inputs.runs-on }}
+    env:
+        quay_username: ${{ secrets.quayUsername }}
     steps:
 
 
@@ -95,7 +97,7 @@ jobs:
           && sudo apt-get install -y git
 
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: Release space from worker
         if: inputs.runs-on == 'ubuntu-latest'
@@ -187,7 +189,7 @@ jobs:
           password: ${{ secrets.dockerPassword }}
 
       - name: Login to Quay.io
-        # if: github.event_name != 'pull_request'
+        if: ${{ env.quay_username != '' }}
         uses: docker/login-action@v3
         with:
           registry: quay.io
@@ -230,7 +232,7 @@ jobs:
           file: ${{ inputs.dockerfile }}
           cache-from: type=gha
           platforms: ${{ inputs.platforms }}
-          push: true
+          push: ${{ env.quay_username != '' }}
           tags: ${{ steps.meta_pull_request.outputs.tags }}
           labels: ${{ steps.meta_pull_request.outputs.labels }}
 
@@ -238,4 +240,4 @@ jobs:
 
       - name: job summary
         run: |
-          echo "Built image: ${{ steps.meta.outputs.labels }}" >> $GITHUB_STEP_SUMMARY 
+          echo "Built image: ${{ steps.meta.outputs.labels }}" >> $GITHUB_STEP_SUMMARY

.github/workflows/backend_build_darwin.yml

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

.github/workflows/backend_pr.yml

@@ -0,0 +1,78 @@
+name: 'build backend container images (PR-filtered)'
+
+on:
+  pull_request:
+
+concurrency:
+  group: ci-backends-pr-${{ github.head_ref || github.ref }}-${{ github.repository }}
+  cancel-in-progress: true
+
+jobs:
+  generate-matrix:
+    runs-on: ubuntu-latest
+    outputs:
+      matrix: ${{ steps.set-matrix.outputs.matrix }}
+      matrix-darwin: ${{ steps.set-matrix.outputs.matrix-darwin }}
+      has-backends: ${{ steps.set-matrix.outputs.has-backends }}
+      has-backends-darwin: ${{ steps.set-matrix.outputs.has-backends-darwin }}
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v5
+
+      - name: Setup Bun
+        uses: oven-sh/setup-bun@v2
+
+      - name: Install dependencies
+        run: |
+          bun add js-yaml
+          bun add @octokit/core
+
+      # filters the matrix in backend.yml
+      - name: Filter matrix for changed backends
+        id: set-matrix
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          GITHUB_EVENT_PATH: ${{ github.event_path }}
+        run: bun run scripts/changed-backends.js
+
+  backend-jobs:
+    needs: generate-matrix
+    uses: ./.github/workflows/backend_build.yml
+    if: needs.generate-matrix.outputs.has-backends == 'true'
+    with:
+      tag-latest: ${{ matrix.tag-latest }}
+      tag-suffix: ${{ matrix.tag-suffix }}
+      build-type: ${{ matrix.build-type }}
+      cuda-major-version: ${{ matrix.cuda-major-version }}
+      cuda-minor-version: ${{ matrix.cuda-minor-version }}
+      platforms: ${{ matrix.platforms }}
+      runs-on: ${{ matrix.runs-on }}
+      base-image: ${{ matrix.base-image }}
+      backend: ${{ matrix.backend }}
+      dockerfile: ${{ matrix.dockerfile }}
+      skip-drivers: ${{ matrix.skip-drivers }}
+      context: ${{ matrix.context }}
+    secrets:
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+    strategy:
+      fail-fast: true
+      matrix: ${{ fromJson(needs.generate-matrix.outputs.matrix) }}
+  backend-jobs-darwin:
+    needs: generate-matrix
+    uses: ./.github/workflows/backend_build_darwin.yml
+    if: needs.generate-matrix.outputs.has-backends-darwin == 'true'
+    with:
+      backend: ${{ matrix.backend }}
+      build-type: ${{ matrix.build-type }}
+      go-version: "1.24.x"
+      tag-suffix: ${{ matrix.tag-suffix }}
+      lang: ${{ matrix.lang || 'python' }}
+      use-pip: ${{ matrix.backend == 'diffusers' }}
+      runs-on: "macOS-14"
+    secrets:
+      quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+      quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
+    strategy:
+      fail-fast: true
+      matrix: ${{ fromJson(needs.generate-matrix.outputs.matrix-darwin) }}

.github/workflows/build-test.yaml

@@ -11,13 +11,57 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           fetch-depth: 0
       - name: Set up Go
         uses: actions/setup-go@v5
         with:
-          go-version: 1.23
+          go-version: 1.25
       - name: Run GoReleaser
         run: |
           make dev-dist
+  launcher-build-darwin:
+    runs-on: macos-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v5
+        with:
+          fetch-depth: 0
+      - name: Set up Go
+        uses: actions/setup-go@v5
+        with:
+          go-version: 1.25
+      - name: Build launcher for macOS ARM64
+        run: |
+          make build-launcher-darwin
+          ls -liah dist
+      - name: Upload macOS launcher artifacts
+        uses: actions/upload-artifact@v5
+        with:
+          name: launcher-macos
+          path: dist/
+          retention-days: 30
+      
+  launcher-build-linux:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v5
+        with:
+          fetch-depth: 0
+      - name: Set up Go
+        uses: actions/setup-go@v5
+        with:
+          go-version: 1.25
+      - name: Build launcher for Linux
+        run: |
+          sudo apt-get update
+          sudo apt-get install golang gcc libgl1-mesa-dev xorg-dev libxkbcommon-dev
+          make build-launcher-linux
+      - name: Upload Linux launcher artifacts
+        uses: actions/upload-artifact@v5
+        with:
+          name: launcher-linux
+          path: local-ai-launcher-linux.tar.xz
+          retention-days: 30

.github/workflows/bump_deps.yaml

@@ -1,10 +1,10 @@
-name: Bump dependencies
+name: Bump Backend dependencies
 on:
   schedule:
     - cron: 0 20 * * *
   workflow_dispatch:
 jobs:
-  bump:
+  bump-backends:
     strategy:
       fail-fast: false
       matrix:
@@ -31,7 +31,7 @@ jobs:
             file: "backend/go/piper/Makefile"
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - name: Bump dependencies 🔧
         id: bump
         run: |

.github/workflows/bump_docs.yaml

@@ -1,10 +1,10 @@
-name: Bump dependencies
+name: Bump Documentation
 on:
   schedule:
     - cron: 0 20 * * *
   workflow_dispatch:
 jobs:
-  bump:
+  bump-docs:
     strategy:
       fail-fast: false
       matrix:
@@ -12,7 +12,7 @@ jobs:
           - repository: "mudler/LocalAI"
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - name: Bump dependencies 🔧
         run: |
           bash .github/bump_docs.sh ${{ matrix.repository }}

.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@v4
+      - uses: actions/checkout@v5
       - name: Install dependencies
         run: |
           sudo apt-get update

.github/workflows/dependabot_auto.yml

@@ -20,7 +20,7 @@ jobs:
           skip-commit-verification: true
 
       - name: Checkout repository
-        uses: actions/checkout@v4
+        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@v4
+        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@v1.2.2
+        uses: appleboy/ssh-action@v1.2.3
         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@v1.2.2
+        uses: appleboy/ssh-action@v1.2.3
         with:
             host: ${{ secrets.EXPLORER_SSH_HOST }}
             username: ${{ secrets.EXPLORER_SSH_USERNAME }}

.github/workflows/gallery-agent.yaml

@@ -0,0 +1,119 @@
+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@v5
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Set up Go
+        uses: actions/setup-go@v5
+        with:
+          go-version: '1.21'
+
+
+      - name: Run gallery agent
+        env:
+          OPENAI_MODEL: ${{ secrets.OPENAI_MODEL }}
+          OPENAI_KEY: ${{ secrets.OPENAI_KEY }}
+          OPENAI_BASE_URL: ${{ secrets.OPENAI_BASE_URL }}
+          SEARCH_TERM: ${{ github.event.inputs.search_term || 'GGUF' }}
+          LIMIT: ${{ github.event.inputs.limit || '15' }}
+          QUANTIZATION: ${{ github.event.inputs.quantization || 'Q4_K_M' }}
+          MAX_MODELS: ${{ github.event.inputs.max_models || '1' }}
+        run: |
+          export GALLERY_INDEX_PATH=$PWD/gallery/index.yaml
+          go run .github/gallery-agent
+
+      - name: Check for changes
+        id: check_changes
+        run: |
+          if git diff --quiet gallery/index.yaml; then
+            echo "changes=false" >> $GITHUB_OUTPUT
+            echo "No changes detected in gallery/index.yaml"
+          else
+            echo "changes=true" >> $GITHUB_OUTPUT
+            echo "Changes detected in gallery/index.yaml"
+            git diff gallery/index.yaml
+          fi
+
+      - name: Read gallery agent summary
+        id: read_summary
+        if: steps.check_changes.outputs.changes == 'true'
+        run: |
+          if [ -f ".github/gallery-agent/gallery-agent-summary.json" ]; then
+            echo "summary_exists=true" >> $GITHUB_OUTPUT
+            # Extract summary data using jq
+            echo "search_term=$(jq -r '.search_term' .github/gallery-agent/gallery-agent-summary.json)" >> $GITHUB_OUTPUT
+            echo "total_found=$(jq -r '.total_found' .github/gallery-agent/gallery-agent-summary.json)" >> $GITHUB_OUTPUT
+            echo "models_added=$(jq -r '.models_added' .github/gallery-agent/gallery-agent-summary.json)" >> $GITHUB_OUTPUT
+            echo "quantization=$(jq -r '.quantization' .github/gallery-agent/gallery-agent-summary.json)" >> $GITHUB_OUTPUT
+            echo "processing_time=$(jq -r '.processing_time' .github/gallery-agent/gallery-agent-summary.json)" >> $GITHUB_OUTPUT
+            
+            # Create a formatted list of added models with URLs
+            added_models=$(jq -r 'range(0; .added_model_ids | length) as $i | "- [\(.added_model_ids[$i])](\(.added_model_urls[$i]))"' .github/gallery-agent/gallery-agent-summary.json | tr '\n' '\n')
+            echo "added_models<<EOF" >> $GITHUB_OUTPUT
+            echo "$added_models" >> $GITHUB_OUTPUT
+            echo "EOF" >> $GITHUB_OUTPUT
+            rm -f .github/gallery-agent/gallery-agent-summary.json
+          else
+            echo "summary_exists=false" >> $GITHUB_OUTPUT
+          fi
+
+      - name: Create Pull Request
+        if: steps.check_changes.outputs.changes == 'true'
+        uses: peter-evans/create-pull-request@v7
+        with:
+          token: ${{ secrets.UPDATE_BOT_TOKEN }}
+          push-to-fork: ci-forks/LocalAI
+          commit-message: 'chore(model gallery): :robot: add new models via gallery agent'
+          title: 'chore(model gallery): :robot: add ${{ steps.read_summary.outputs.models_added || 0 }} new models via gallery agent'
+          # Branch has to be unique so PRs are not overriding each other
+          branch-suffix: timestamp
+          body: |
+            This PR was automatically created by the gallery agent workflow.
+            
+            **Summary:**
+            - **Search Term:** ${{ steps.read_summary.outputs.search_term || github.event.inputs.search_term || 'GGUF' }}
+            - **Models Found:** ${{ steps.read_summary.outputs.total_found || 'N/A' }}
+            - **Models Added:** ${{ steps.read_summary.outputs.models_added || '0' }}
+            - **Quantization:** ${{ steps.read_summary.outputs.quantization || github.event.inputs.quantization || 'Q4_K_M' }}
+            - **Processing Time:** ${{ steps.read_summary.outputs.processing_time || 'N/A' }}
+            
+            **Added Models:**
+            ${{ steps.read_summary.outputs.added_models || '- No models added' }}
+            
+            **Workflow Details:**
+            - Triggered by: `${{ github.event_name }}`
+            - Run ID: `${{ github.run_id }}`
+            - Commit: `${{ github.sha }}`
+          signoff: true
+          delete-branch: true

.github/workflows/generate_grpc_cache.yaml

@@ -73,7 +73,7 @@ jobs:
         uses: docker/setup-buildx-action@master
 
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: Cache GRPC
         uses: docker/build-push-action@v6

.github/workflows/generate_intel_image.yaml

@@ -43,7 +43,7 @@ jobs:
         uses: docker/setup-buildx-action@master
 
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: Cache Intel images
         uses: docker/build-push-action@v6

.github/workflows/image-pr.yml

@@ -47,16 +47,16 @@ jobs:
             platforms: 'linux/amd64'
             tag-latest: 'false'
             tag-suffix: '-hipblas'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            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_f16'
+          - 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-f16'
+            tag-suffix: 'sycl'
             runs-on: 'ubuntu-latest'
             makeflags: "--jobs=3 --output-sync=target"
           - build-type: 'vulkan'

.github/workflows/image.yml

@@ -39,7 +39,7 @@ jobs:
             platforms: 'linux/amd64'
             tag-latest: 'auto'
             tag-suffix: '-gpu-hipblas'
-            base-image: "rocm/dev-ubuntu-22.04:6.1"
+            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"
@@ -109,24 +109,15 @@ jobs:
             skip-drivers: 'false'
             makeflags: "--jobs=4 --output-sync=target"
             aio: "-aio-gpu-vulkan"
-          - build-type: 'sycl_f16'
+          - 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-f16'
+            tag-suffix: '-gpu-intel'
             runs-on: 'ubuntu-latest'
             makeflags: "--jobs=3 --output-sync=target"
-            aio: "-aio-gpu-intel-f16"
-          - build-type: 'sycl_f32'
-            platforms: 'linux/amd64'
-            tag-latest: 'auto'
-            base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
-            grpc-base-image: "ubuntu:22.04"
-            tag-suffix: '-gpu-intel-f32'
-            runs-on: 'ubuntu-latest'
-            makeflags: "--jobs=3 --output-sync=target"
-            aio: "-aio-gpu-intel-f32"
+            aio: "-aio-gpu-intel"
 
   gh-runner:
     uses: ./.github/workflows/image_build.yml

.github/workflows/image_build.yml

@@ -94,7 +94,7 @@ jobs:
           && sudo apt-get update \
           && sudo apt-get install -y git
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: Release space from worker
         if: inputs.runs-on == 'ubuntu-latest'

.github/workflows/labeler.yml

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

.github/workflows/localaibot_automerge.yml

@@ -6,14 +6,15 @@ 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' }}
+    if: ${{ github.actor == 'localai-bot' && !contains(github.event.pull_request.title, 'chore(model gallery):') }}
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: Approve a PR if not already approved
         run: |

.github/workflows/notify-models.yaml

@@ -1,22 +1,27 @@
 name: Notifications for new models
 on:
-  pull_request:
+  pull_request_target:
      types:
        - closed
 
+permissions:
+  contents: read
+  pull-requests: read
+
 jobs:
   notify-discord:
     if: ${{ (github.event.pull_request.merged == true) && (contains(github.event.pull_request.labels.*.name, 'area/ai-model')) }}
     env:
-        MODEL_NAME: gemma-3-12b-it
+        MODEL_NAME: gemma-3-12b-it-qat
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v4
+    - 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' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
+        model: 'gemma-3-12b-it-qat' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
         # Check the PR diff using the current branch and the base branch of the PR
     - uses: GrantBirki/git-diff-action@v2.8.1
       id: git-diff-action
@@ -79,7 +84,7 @@ jobs:
         args: ${{ steps.summarize.outputs.message }}
     - name: Setup tmate session if fails
       if: ${{ failure() }}
-      uses: mxschmitt/action-tmate@v3.22
+      uses: mxschmitt/action-tmate@v3.23
       with:
         detached: true
         connect-timeout-seconds: 180
@@ -87,12 +92,13 @@ 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
+        MODEL_NAME: gemma-3-12b-it-qat
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v4
+    - 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..."
@@ -161,7 +167,7 @@ jobs:
         TWITTER_ACCESS_TOKEN_SECRET: ${{ secrets.TWITTER_ACCESS_TOKEN_SECRET }}
     - name: Setup tmate session if fails
       if: ${{ failure() }}
-      uses: mxschmitt/action-tmate@v3.22
+      uses: mxschmitt/action-tmate@v3.23
       with:
         detached: true
         connect-timeout-seconds: 180

.github/workflows/notify-releases.yaml

@@ -11,10 +11,11 @@ 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' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
+        model: 'gemma-3-12b-it-qat' # 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@v4
+        uses: actions/checkout@v5
         with:
           fetch-depth: 0
       - name: Set up Go
@@ -23,4 +23,42 @@ jobs:
           version: v2.11.0
           args: release --clean
         env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} 
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+  launcher-build-darwin:
+    runs-on: macos-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v5
+        with:
+          fetch-depth: 0
+      - name: Set up Go
+        uses: actions/setup-go@v5
+        with:
+          go-version: 1.23
+      - name: Build launcher for macOS ARM64
+        run: |
+          make build-launcher-darwin
+      - name: Upload DMG to Release
+        uses: softprops/action-gh-release@v2
+        with:
+          files: ./dist/LocalAI.dmg
+  launcher-build-linux:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v5
+        with:
+          fetch-depth: 0
+      - name: Set up Go
+        uses: actions/setup-go@v5
+        with:
+          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: softprops/action-gh-release@v2
+        with:
+          files: ./local-ai-launcher-linux.tar.xz

.github/workflows/secscan.yaml

@@ -14,17 +14,17 @@ jobs:
       GO111MODULE: on
     steps:
       - name: Checkout Source
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         if: ${{ github.actor != 'dependabot[bot]' }}
       - name: Run Gosec Security Scanner
         if: ${{ github.actor != 'dependabot[bot]' }}
-        uses: securego/gosec@v2.22.7
+        uses: securego/gosec@v2.22.9
         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@v3
+        uses: github/codeql-action/upload-sarif@v4
         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@5bef64f19d7facfb25b37b414482c7164d639639 # v9
+      - uses: actions/stale@5f858e3efba33a5ca4407a664cc011ad407f2008 # 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@v4
+  #       uses: actions/checkout@v5
   #       with:
   #         submodules: true
   #     - name: Dependencies
@@ -40,7 +40,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Dependencies
@@ -61,7 +61,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Dependencies
@@ -83,7 +83,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Dependencies
@@ -104,7 +104,7 @@ jobs:
   #  runs-on: ubuntu-latest
   #  steps:
   #    - name: Clone
-  #      uses: actions/checkout@v4
+  #      uses: actions/checkout@v5
   #      with:
   #        submodules: true
   #    - name: Dependencies
@@ -124,7 +124,7 @@ jobs:
   #   runs-on: ubuntu-latest
   #   steps:
   #     - name: Clone
-  #       uses: actions/checkout@v4
+  #       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@v4
+  #       uses: actions/checkout@v5
   #       with:
   #         submodules: true
   #     - name: Dependencies
@@ -211,7 +211,7 @@ jobs:
   #   runs-on: ubuntu-latest
   #   steps:
   #     - name: Clone
-  #       uses: actions/checkout@v4
+  #       uses: actions/checkout@v5
   #       with:
   #         submodules: true
   #     - name: Dependencies
@@ -232,7 +232,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Dependencies

.github/workflows/test.yml

@@ -21,8 +21,22 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        go-version: ['1.21.x']
+        go-version: ['1.25.x']
     steps:
+      - name: Free Disk Space (Ubuntu)
+        uses: jlumbroso/free-disk-space@main
+        with:
+          # this might remove tools that are actually needed,
+          # if set to "true" but frees about 6 GB
+          tool-cache: true
+          # all of these default to true, but feel free to set to
+          # "false" if necessary for your workflow
+          android: true
+          dotnet: true
+          haskell: true
+          large-packages: true
+          docker-images: true
+          swap-storage: true
       - name: Release space from worker
         run: |
           echo "Listing top largest packages"
@@ -56,7 +70,7 @@ jobs:
           sudo rm -rfv build || true
           df -h
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Setup Go ${{ matrix.go-version }}
@@ -110,7 +124,7 @@ jobs:
           PATH="$PATH:/root/go/bin" GO_TAGS="tts" make --jobs 5 --output-sync=target test
       - name: Setup tmate session if tests fail
         if: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.22
+        uses: mxschmitt/action-tmate@v3.23
         with:
           detached: true
           connect-timeout-seconds: 180
@@ -152,7 +166,7 @@ jobs:
           sudo rm -rfv build || true
           df -h
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Dependencies
@@ -169,7 +183,7 @@ jobs:
             PATH="$PATH:$HOME/go/bin" make backends/local-store backends/silero-vad backends/llama-cpp backends/whisper backends/piper backends/stablediffusion-ggml docker-build-aio e2e-aio
       - name: Setup tmate session if tests fail
         if: ${{ failure() }}
-        uses: mxschmitt/action-tmate@v3.22
+        uses: mxschmitt/action-tmate@v3.23
         with:
           detached: true
           connect-timeout-seconds: 180
@@ -179,10 +193,10 @@ jobs:
     runs-on: macOS-14
     strategy:
       matrix:
-        go-version: ['1.21.x']
+        go-version: ['1.25.x']
     steps:
       - name: Clone
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           submodules: true
       - name: Setup Go ${{ matrix.go-version }}
@@ -200,11 +214,7 @@ jobs:
       - name: Build llama-cpp-darwin
         run: |
           make protogen-go
-          make build
-          bash scripts/build-llama-cpp-darwin.sh
-          ls -la build/darwin.tar
-          mv build/darwin.tar build/llama-cpp.tar
-          ./local-ai backends install "ocifile://$PWD/build/llama-cpp.tar"
+          make backends/llama-cpp-darwin
       - name: Test
         run: |
           export C_INCLUDE_PATH=/usr/local/include
@@ -216,7 +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@v3.22
+        uses: mxschmitt/action-tmate@v3.23
         with:
           detached: true
           connect-timeout-seconds: 180

.github/workflows/update_swagger.yaml

@@ -9,7 +9,7 @@ jobs:
       fail-fast: false
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - uses: actions/setup-go@v5
         with:
           go-version: 'stable'

.gitignore

@@ -24,7 +24,7 @@ go-bert
 
 # LocalAI build binary
 LocalAI
-local-ai
+/local-ai
 # prevent above rules from omitting the helm chart
 !charts/*
 # prevent above rules from omitting the api/localai folder

.gitmodules

@@ -1,6 +1,3 @@
 [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

@@ -8,7 +8,7 @@ source:
   enabled: true
   name_template: '{{ .ProjectName }}-{{ .Tag }}-source'
 builds:
-  -
+  - main: ./cmd/local-ai
     env:
       - CGO_ENABLED=0
     ldflags:

CONTRIBUTING.md

@@ -30,6 +30,7 @@ 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
 
@@ -76,7 +77,7 @@ LOCALAI_IMAGE_TAG=test LOCALAI_IMAGE=local-ai-aio make run-e2e-aio
 ## Documentation
 
 We are welcome the contribution of the documents, please open new PR or create a new issue. The documentation is available under `docs/` https://github.com/mudler/LocalAI/tree/master/docs
- 
+
 ## Community and Communication
 
 - You can reach out via the Github issue tracker.

Dockerfile

@@ -9,7 +9,7 @@ ENV DEBIAN_FRONTEND=noninteractive
 RUN apt-get update && \
     apt-get install -y --no-install-recommends \
         ca-certificates curl wget espeak-ng libgomp1 \
-        python3 python-is-python3 ffmpeg && \
+        ffmpeg libopenblas-base libopenblas-dev && \
     apt-get clean && \
     rm -rf /var/lib/apt/lists/*
 
@@ -78,6 +78,16 @@ RUN <<EOT bash
     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-ubuntu2204-0.6.0_0.6.0-1_arm64.deb && \
+        dpkg -i cudss-local-tegra-repo-ubuntu2204-0.6.0_0.6.0-1_arm64.deb && \
+        cp /var/cudss-local-tegra-repo-ubuntu2204-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
+        apt-get update && apt-get -y install cudss
+    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 && \
@@ -100,6 +110,12 @@ RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
         ldconfig \
     ; fi
 
+RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
+    ln -s /opt/rocm-**/lib/llvm/lib/libomp.so /usr/lib/libomp.so \
+    ; fi
+
+RUN expr "${BUILD_TYPE}" = intel && echo "intel" > /run/localai/capability || echo "not intel"
+
 # Cuda
 ENV PATH=/usr/local/cuda/bin:${PATH}
 

Makefile

@@ -2,11 +2,10 @@ GOCMD=go
 GOTEST=$(GOCMD) test
 GOVET=$(GOCMD) vet
 BINARY_NAME=local-ai
+LAUNCHER_BINARY_NAME=local-ai-launcher
 
 GORELEASER?=
 
-ONEAPI_VERSION?=2025.2
-
 export BUILD_TYPE?=
 
 GO_TAGS?=
@@ -92,7 +91,21 @@ build: protogen-go install-go-tools ## Build the project
 	$(info ${GREEN}I LD_FLAGS: ${YELLOW}$(LD_FLAGS)${RESET})
 	$(info ${GREEN}I UPX: ${YELLOW}$(UPX)${RESET})
 	rm -rf $(BINARY_NAME) || true
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(BINARY_NAME) ./
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(BINARY_NAME) ./cmd/local-ai
+
+build-launcher: ## Build the launcher application
+	$(info ${GREEN}I local-ai launcher build info:${RESET})
+	$(info ${GREEN}I BUILD_TYPE: ${YELLOW}$(BUILD_TYPE)${RESET})
+	$(info ${GREEN}I GO_TAGS: ${YELLOW}$(GO_TAGS)${RESET})
+	$(info ${GREEN}I LD_FLAGS: ${YELLOW}$(LD_FLAGS)${RESET})
+	rm -rf $(LAUNCHER_BINARY_NAME) || true
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(LAUNCHER_BINARY_NAME) ./cmd/launcher
+
+build-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:
 	$(GORELEASER) build --snapshot --clean
@@ -108,8 +121,8 @@ run: ## run local-ai
 	CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) run ./
 
 test-models/testmodel.ggml:
-	mkdir test-models
-	mkdir test-dir
+	mkdir -p test-models
+	mkdir -p test-dir
 	wget -q https://huggingface.co/mradermacher/gpt2-alpaca-gpt4-GGUF/resolve/main/gpt2-alpaca-gpt4.Q4_K_M.gguf -O test-models/testmodel.ggml
 	wget -q https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin -O test-models/whisper-en
 	wget -q https://huggingface.co/mudler/all-MiniLM-L6-v2/resolve/main/ggml-model-q4_0.bin -O test-models/bert
@@ -134,30 +147,6 @@ test: test-models/testmodel.ggml protogen-go
 	$(MAKE) test-tts
 	$(MAKE) test-stablediffusion
 
-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)"
-
 ########################################################
 ## AIO tests
 ########################################################
@@ -340,24 +329,86 @@ docker-aio-all:
 
 docker-image-intel:
 	docker build \
-		--build-arg BASE_IMAGE=intel/oneapi-basekit:${ONEAPI_VERSION}.0-0-devel-ubuntu24.04 \
+		--build-arg BASE_IMAGE=quay.io/go-skynet/intel-oneapi-base:latest \
 		--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
 		--build-arg GO_TAGS="$(GO_TAGS)" \
 		--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
-		--build-arg BUILD_TYPE=sycl_f32 -t $(DOCKER_IMAGE) .
-
-docker-image-intel-xpu:
-	docker build \
-		--build-arg BASE_IMAGE=intel/oneapi-basekit:${ONEAPI_VERSION}.0-0-devel-ubuntu22.04 \
-		--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
-		--build-arg GO_TAGS="$(GO_TAGS)" \
-		--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
-		--build-arg BUILD_TYPE=sycl_f32 -t $(DOCKER_IMAGE) .
+		--build-arg BUILD_TYPE=intel -t $(DOCKER_IMAGE) .
 
 ########################################################
 ## Backends
 ########################################################
 
+
+backends/diffusers: docker-build-diffusers docker-save-diffusers build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/diffusers.tar)"
+
+backends/llama-cpp: docker-build-llama-cpp docker-save-llama-cpp build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/llama-cpp.tar)"
+
+backends/piper: docker-build-piper docker-save-piper build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/piper.tar)"
+
+backends/stablediffusion-ggml: docker-build-stablediffusion-ggml docker-save-stablediffusion-ggml build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/stablediffusion-ggml.tar)"
+
+backends/whisper: docker-build-whisper docker-save-whisper build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/whisper.tar)"
+
+backends/silero-vad: docker-build-silero-vad docker-save-silero-vad build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/silero-vad.tar)"
+
+backends/local-store: docker-build-local-store docker-save-local-store build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/local-store.tar)"
+
+backends/huggingface: docker-build-huggingface docker-save-huggingface build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/huggingface.tar)"
+
+backends/rfdetr: docker-build-rfdetr docker-save-rfdetr build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/rfdetr.tar)"
+
+backends/kitten-tts: docker-build-kitten-tts docker-save-kitten-tts build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/kitten-tts.tar)"
+
+backends/kokoro: docker-build-kokoro docker-save-kokoro build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/kokoro.tar)"
+
+backends/chatterbox: docker-build-chatterbox docker-save-chatterbox build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/chatterbox.tar)"
+
+backends/llama-cpp-darwin: build
+	bash ./scripts/build/llama-cpp-darwin.sh
+	./local-ai backends install "ocifile://$(abspath ./backend-images/llama-cpp.tar)"
+
+backends/neutts: docker-build-neutts docker-save-neutts build
+	./local-ai backends install "ocifile://$(abspath ./backend-images/neutts.tar)"
+
+build-darwin-python-backend: build
+	bash ./scripts/build/python-darwin.sh
+
+build-darwin-go-backend: build
+	bash ./scripts/build/golang-darwin.sh
+
+backends/mlx:
+	BACKEND=mlx $(MAKE) build-darwin-python-backend
+	./local-ai backends install "ocifile://$(abspath ./backend-images/mlx.tar)"
+
+backends/diffuser-darwin:
+	BACKEND=diffusers $(MAKE) build-darwin-python-backend
+	./local-ai backends install "ocifile://$(abspath ./backend-images/diffusers.tar)"
+
+backends/mlx-vlm:
+	BACKEND=mlx-vlm $(MAKE) build-darwin-python-backend
+	./local-ai backends install "ocifile://$(abspath ./backend-images/mlx-vlm.tar)"
+
+backends/mlx-audio:
+	BACKEND=mlx-audio $(MAKE) build-darwin-python-backend
+	./local-ai backends install "ocifile://$(abspath ./backend-images/mlx-audio.tar)"
+
+backends/stablediffusion-ggml-darwin:
+	BACKEND=stablediffusion-ggml BUILD_TYPE=metal $(MAKE) build-darwin-go-backend
+	./local-ai backends install "ocifile://$(abspath ./backend-images/stablediffusion-ggml.tar)"
+
 backend-images:
 	mkdir -p backend-images
 
@@ -379,6 +430,27 @@ docker-build-huggingface:
 docker-build-rfdetr:
 	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:rfdetr -f backend/Dockerfile.python --build-arg BACKEND=rfdetr ./backend
 
+docker-build-kitten-tts:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:kitten-tts -f backend/Dockerfile.python --build-arg BACKEND=kitten-tts ./backend
+
+docker-save-kitten-tts: backend-images
+	docker save local-ai-backend:kitten-tts -o backend-images/kitten-tts.tar
+
+docker-save-chatterbox: backend-images
+	docker save local-ai-backend:chatterbox -o backend-images/chatterbox.tar
+
+docker-build-neutts:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:neutts -f backend/Dockerfile.python --build-arg BACKEND=neutts ./backend
+
+docker-save-neutts: backend-images
+	docker save local-ai-backend:neutts -o backend-images/neutts.tar
+
+docker-build-kokoro:
+	docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:kokoro -f backend/Dockerfile.python --build-arg BACKEND=kokoro ./backend
+
+docker-save-kokoro: backend-images
+	docker save local-ai-backend:kokoro -o backend-images/kokoro.tar
+
 docker-save-rfdetr: backend-images
 	docker save local-ai-backend:rfdetr -o backend-images/rfdetr.tar
 
@@ -419,10 +491,10 @@ 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 --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 .
+	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-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 .
+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  .
@@ -440,7 +512,7 @@ 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 .
+	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 .
@@ -476,3 +548,19 @@ docs-clean:
 .PHONY: docs
 docs: docs/static/gallery.html
 	cd docs && hugo serve
+
+########################################################
+## Platform-specific builds
+########################################################
+
+## fyne cross-platform build
+build-launcher-darwin: build-launcher
+	go run github.com/tiagomelo/macos-dmg-creator/cmd/createdmg@latest \
+	--appName "LocalAI" \
+	--appBinaryPath "$(LAUNCHER_BINARY_NAME)" \
+	--bundleIdentifier "com.localai.launcher" \
+	--iconPath "core/http/static/logo.png" \
+	--outputDir "dist/"
+
+build-launcher-linux:
+	cd cmd/launcher && go run fyne.io/tools/cmd/fyne@latest package -os linux -icon ../../core/http/static/logo.png --executable $(LAUNCHER_BINARY_NAME)-linux && mv launcher.tar.xz ../../$(LAUNCHER_BINARY_NAME)-linux.tar.xz

README.md

@@ -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) [🥽 Demo](https://demo.localai.io) [🌍 Explorer](https://explorer.localai.io) [🛫 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) [🛫 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)
@@ -110,8 +110,23 @@ curl https://localai.io/install.sh | sh
 
 For more installation options, see [Installer Options](https://localai.io/docs/advanced/installer/).
 
+### macOS Download:
+
+<a href="https://github.com/mudler/LocalAI/releases/latest/download/LocalAI.dmg">
+  <img src="https://img.shields.io/badge/Download-macOS-blue?style=for-the-badge&logo=apple&logoColor=white" alt="Download LocalAI for macOS"/>
+</a>
+
+> Note: the DMGs are not signed by Apple as quarantined. See https://github.com/mudler/LocalAI/issues/6268 for a workaround, fix is tracked here: https://github.com/mudler/LocalAI/issues/6244
+
 Or run with docker:
 
+> **💡 Docker Run vs Docker Start**
+> 
+> - `docker run` creates and starts a new container. If a container with the same name already exists, this command will fail.
+> - `docker start` starts an existing container that was previously created with `docker run`.
+> 
+> If you've already run LocalAI before and want to start it again, use: `docker start -i local-ai`
+
 ### CPU only image:
 
 ```bash
@@ -140,11 +155,7 @@ docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri
 ### Intel GPU Images (oneAPI):
 
 ```bash
-# Intel GPU with FP16 support
-docker run -ti --name local-ai -p 8080:8080 --device=/dev/dri/card1 --device=/dev/dri/renderD128 localai/localai:latest-gpu-intel-f16
-
-# Intel GPU with FP32 support
-docker run -ti --name local-ai -p 8080:8080 --device=/dev/dri/card1 --device=/dev/dri/renderD128 localai/localai:latest-gpu-intel-f32
+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:
@@ -166,7 +177,7 @@ docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-ai
 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-f16
+docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-gpu-intel
 
 # AMD GPU version
 docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri --group-add=video localai/localai:latest-aio-gpu-hipblas
@@ -191,10 +202,13 @@ 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)
+For more information, see [💻 Getting started](https://localai.io/basics/getting_started/index.html), if you are interested in our roadmap items and future enhancements, you can see the [Issues labeled as Roadmap here](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
 
 ## 📰 Latest project news
 
+- October 2025: 🔌 [Model Context Protocol (MCP)](https://localai.io/docs/features/mcp/) support added for agentic capabilities with external tools
+- September 2025: New Launcher application for MacOS and Linux, extended support to many backends for Mac and Nvidia L4T devices. Models: Added MLX-Audio, WAN 2.2. WebUI improvements and Python-based backends now ships portable python environments.
+- August 2025: MLX, MLX-VLM, Diffusers and llama.cpp are now supported on Mac M1/M2/M3+ chips ( with `development` suffix in the gallery ): https://github.com/mudler/LocalAI/pull/6049 https://github.com/mudler/LocalAI/pull/6119 https://github.com/mudler/LocalAI/pull/6121 https://github.com/mudler/LocalAI/pull/6060
 - July/August 2025: 🔍 [Object Detection](https://localai.io/features/object-detection/) added to the API featuring [rf-detr](https://github.com/roboflow/rf-detr)
 - July 2025: All backends migrated outside of the main binary. LocalAI is now more lightweight, small, and automatically downloads the required backend to run the model. [Read the release notes](https://github.com/mudler/LocalAI/releases/tag/v3.2.0)
 - June 2025: [Backend management](https://github.com/mudler/LocalAI/pull/5607) has been added. Attention: extras images are going to be deprecated from the next release! Read [the backend management PR](https://github.com/mudler/LocalAI/pull/5607).
@@ -232,10 +246,65 @@ 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/)
-- [Agentic capabilities](https://github.com/mudler/LocalAGI)
+- 🆕🔌 [Model Context Protocol (MCP)](https://localai.io/docs/features/mcp/) - Agentic capabilities with external tools and [LocalAGI's Agentic capabilities](https://github.com/mudler/LocalAGI)
 - 🔊 Voice activity detection (Silero-VAD support)
 - 🌍 Integrated WebUI!
 
+## 🧩 Supported Backends & Acceleration
+
+LocalAI supports a comprehensive range of AI backends with multiple acceleration options:
+
+### Text Generation & Language Models
+| Backend | Description | Acceleration Support |
+|---------|-------------|---------------------|
+| **llama.cpp** | LLM inference in C/C++ | CUDA 11/12, ROCm, Intel SYCL, Vulkan, Metal, CPU |
+| **vLLM** | Fast LLM inference with PagedAttention | CUDA 12, ROCm, Intel |
+| **transformers** | HuggingFace transformers framework | CUDA 11/12, ROCm, Intel, CPU |
+| **exllama2** | GPTQ inference library | CUDA 12 |
+| **MLX** | Apple Silicon LLM inference | Metal (M1/M2/M3+) |
+| **MLX-VLM** | Apple Silicon Vision-Language Models | Metal (M1/M2/M3+) |
+
+### Audio & Speech Processing
+| Backend | Description | Acceleration Support |
+|---------|-------------|---------------------|
+| **whisper.cpp** | OpenAI Whisper in C/C++ | CUDA 12, ROCm, Intel SYCL, Vulkan, CPU |
+| **faster-whisper** | Fast Whisper with CTranslate2 | CUDA 12, ROCm, Intel, CPU |
+| **bark** | Text-to-audio generation | CUDA 12, ROCm, Intel |
+| **bark-cpp** | C++ implementation of Bark | CUDA, Metal, CPU |
+| **coqui** | Advanced TTS with 1100+ languages | CUDA 12, ROCm, Intel, CPU |
+| **kokoro** | Lightweight TTS model | CUDA 12, ROCm, Intel, CPU |
+| **chatterbox** | Production-grade TTS | CUDA 11/12, CPU |
+| **piper** | Fast neural TTS system | CPU |
+| **kitten-tts** | Kitten TTS models | CPU |
+| **silero-vad** | Voice Activity Detection | CPU |
+| **neutts** | Text-to-speech with voice cloning | CUDA 12, ROCm, CPU |
+
+### Image & Video Generation
+| Backend | Description | Acceleration Support |
+|---------|-------------|---------------------|
+| **stablediffusion.cpp** | Stable Diffusion in C/C++ | CUDA 12, Intel SYCL, Vulkan, CPU |
+| **diffusers** | HuggingFace diffusion models | CUDA 11/12, ROCm, Intel, Metal, CPU |
+
+### Specialized AI Tasks
+| Backend | Description | Acceleration Support |
+|---------|-------------|---------------------|
+| **rfdetr** | Real-time object detection | CUDA 12, Intel, CPU |
+| **rerankers** | Document reranking API | CUDA 11/12, ROCm, Intel, CPU |
+| **local-store** | Vector database | CPU |
+| **huggingface** | HuggingFace API integration | API-based |
+
+### Hardware Acceleration Matrix
+
+| Acceleration Type | Supported Backends | Hardware Support |
+|-------------------|-------------------|------------------|
+| **NVIDIA CUDA 11** | llama.cpp, whisper, stablediffusion, diffusers, rerankers, bark, chatterbox | Nvidia hardware |
+| **NVIDIA CUDA 12** | All CUDA-compatible backends | Nvidia hardware |
+| **AMD ROCm** | llama.cpp, whisper, vllm, transformers, diffusers, rerankers, coqui, kokoro, bark, neutts | AMD Graphics |
+| **Intel oneAPI** | llama.cpp, whisper, stablediffusion, vllm, transformers, diffusers, rfdetr, rerankers, exllama2, coqui, kokoro, bark | Intel Arc, Intel iGPUs |
+| **Apple Metal** | llama.cpp, whisper, diffusers, MLX, MLX-VLM, bark-cpp | Apple M1/M2/M3+ |
+| **Vulkan** | llama.cpp, whisper, stablediffusion | Cross-platform GPUs |
+| **NVIDIA Jetson** | llama.cpp, whisper, stablediffusion, diffusers, rfdetr | ARM64 embedded AI |
+| **CPU Optimized** | All backends | AVX/AVX2/AVX512, quantization support |
 
 ### 🔗 Community and integrations
 
@@ -247,9 +316,18 @@ WebUIs:
 - https://github.com/go-skynet/LocalAI-frontend
 - QA-Pilot(An interactive chat project that leverages LocalAI LLMs for rapid understanding and navigation of GitHub code repository) https://github.com/reid41/QA-Pilot
 
+Agentic Libraries:
+- https://github.com/mudler/cogito
+
+MCPs:
+- https://github.com/mudler/MCPs
+
 Model galleries
 - https://github.com/go-skynet/model-gallery
 
+Voice:
+- https://github.com/richiejp/VoxInput
+
 Other:
 - Helm chart https://github.com/go-skynet/helm-charts
 - VSCode extension https://github.com/badgooooor/localai-vscode-plugin

aio/cpu/vision.yaml

@@ -2,10 +2,10 @@ context_size: 4096
 f16: true
 backend: llama-cpp
 mmap: true
-mmproj: minicpm-v-2_6-mmproj-f16.gguf
+mmproj: minicpm-v-4_5-mmproj-f16.gguf
 name: gpt-4o
 parameters:
-  model: minicpm-v-2_6-Q4_K_M.gguf
+  model: minicpm-v-4_5-Q4_K_M.gguf
 stopwords:
 - <|im_end|>
 - <dummy32000>
@@ -42,9 +42,9 @@ template:
     <|im_start|>assistant
 
 download_files:
-- filename: minicpm-v-2_6-Q4_K_M.gguf
-  sha256: 3a4078d53b46f22989adbf998ce5a3fd090b6541f112d7e936eb4204a04100b1
-  uri: huggingface://openbmb/MiniCPM-V-2_6-gguf/ggml-model-Q4_K_M.gguf
-- filename: minicpm-v-2_6-mmproj-f16.gguf
-  uri: huggingface://openbmb/MiniCPM-V-2_6-gguf/mmproj-model-f16.gguf
-  sha256: 4485f68a0f1aa404c391e788ea88ea653c100d8e98fe572698f701e5809711fd
+- filename: minicpm-v-4_5-Q4_K_M.gguf
+  sha256: c1c3c33100b15b4caf7319acce4e23c0eb0ce1cbd12f70e8d24f05aa67b7512f
+  uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/ggml-model-Q4_K_M.gguf
+- filename: minicpm-v-4_5-mmproj-f16.gguf
+  uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/mmproj-model-f16.gguf
+  sha256: 7a7225a32e8d453aaa3d22d8c579b5bf833c253f784cdb05c99c9a76fd616df8

aio/gpu-8g/vision.yaml

@@ -2,10 +2,10 @@ context_size: 4096
 backend: llama-cpp
 f16: true
 mmap: true
-mmproj: minicpm-v-2_6-mmproj-f16.gguf
+mmproj: minicpm-v-4_5-mmproj-f16.gguf
 name: gpt-4o
 parameters:
-  model: minicpm-v-2_6-Q4_K_M.gguf
+  model: minicpm-v-4_5-Q4_K_M.gguf
 stopwords:
 - <|im_end|>
 - <dummy32000>
@@ -42,9 +42,9 @@ template:
     <|im_start|>assistant
 
 download_files:
-- filename: minicpm-v-2_6-Q4_K_M.gguf
-  sha256: 3a4078d53b46f22989adbf998ce5a3fd090b6541f112d7e936eb4204a04100b1
-  uri: huggingface://openbmb/MiniCPM-V-2_6-gguf/ggml-model-Q4_K_M.gguf
-- filename: minicpm-v-2_6-mmproj-f16.gguf
-  uri: huggingface://openbmb/MiniCPM-V-2_6-gguf/mmproj-model-f16.gguf
-  sha256: 4485f68a0f1aa404c391e788ea88ea653c100d8e98fe572698f701e5809711fd
+- filename: minicpm-v-4_5-Q4_K_M.gguf
+  sha256: c1c3c33100b15b4caf7319acce4e23c0eb0ce1cbd12f70e8d24f05aa67b7512f
+  uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/ggml-model-Q4_K_M.gguf
+- filename: minicpm-v-4_5-mmproj-f16.gguf
+  uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/mmproj-model-f16.gguf
+  sha256: 7a7225a32e8d453aaa3d22d8c579b5bf833c253f784cdb05c99c9a76fd616df8

aio/intel/vision.yaml

@@ -2,10 +2,10 @@ context_size: 4096
 backend: llama-cpp
 f16: true
 mmap: true
-mmproj: minicpm-v-2_6-mmproj-f16.gguf
+mmproj: minicpm-v-4_5-mmproj-f16.gguf
 name: gpt-4o
 parameters:
-  model: minicpm-v-2_6-Q4_K_M.gguf
+  model: minicpm-v-4_5-Q4_K_M.gguf
 stopwords:
 - <|im_end|>
 - <dummy32000>
@@ -43,9 +43,9 @@ template:
 
 
 download_files:
-- filename: minicpm-v-2_6-Q4_K_M.gguf
-  sha256: 3a4078d53b46f22989adbf998ce5a3fd090b6541f112d7e936eb4204a04100b1
-  uri: huggingface://openbmb/MiniCPM-V-2_6-gguf/ggml-model-Q4_K_M.gguf
-- filename: minicpm-v-2_6-mmproj-f16.gguf
-  uri: huggingface://openbmb/MiniCPM-V-2_6-gguf/mmproj-model-f16.gguf
-  sha256: 4485f68a0f1aa404c391e788ea88ea653c100d8e98fe572698f701e5809711fd
+- filename: minicpm-v-4_5-Q4_K_M.gguf
+  sha256: c1c3c33100b15b4caf7319acce4e23c0eb0ce1cbd12f70e8d24f05aa67b7512f
+  uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/ggml-model-Q4_K_M.gguf
+- filename: minicpm-v-4_5-mmproj-f16.gguf
+  uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/mmproj-model-f16.gguf
+  sha256: 7a7225a32e8d453aaa3d22d8c579b5bf833c253f784cdb05c99c9a76fd616df8

backend/Dockerfile.golang

@@ -96,17 +96,6 @@ RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
         ldconfig \
     ; fi
 
-# Intel oneAPI requirements
-RUN <<EOT bash
-    if [[ "${BUILD_TYPE}" == sycl* ]] && [ "${SKIP_DRIVERS}" = "false" ]; then
-        apt-get update && \
-        apt-get install -y --no-install-recommends \
-            intel-oneapi-runtime-libs && \
-        apt-get clean && \
-        rm -rf /var/lib/apt/lists/*
-    fi
-EOT
-
 # Install Go
 RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
 ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin:/usr/local/bin

backend/Dockerfile.llama-cpp

@@ -197,7 +197,7 @@ EOT
 
 
 # Copy libraries using a script to handle architecture differences
-RUN make -C /LocalAI/backend/cpp/llama-cpp package
+RUN make -BC /LocalAI/backend/cpp/llama-cpp package
 
 
 FROM scratch

backend/Dockerfile.python

@@ -23,12 +23,12 @@ RUN apt-get update && \
         libssl-dev \
         git \
         git-lfs \
-        unzip \
+        unzip clang \
         upx-ucl \
         curl python3-pip \
         python-is-python3 \
         python3-dev llvm \
-        python3-venv make && \
+        python3-venv make cmake && \
     apt-get clean && \
     rm -rf /var/lib/apt/lists/* && \
     pip install --upgrade pip
@@ -116,7 +116,7 @@ COPY python/${BACKEND} /${BACKEND}
 COPY backend.proto /${BACKEND}/backend.proto
 COPY python/common/ /${BACKEND}/common
 
-RUN cd /${BACKEND} && make
+RUN cd /${BACKEND} && PORTABLE_PYTHON=true make
 
 FROM scratch
 ARG BACKEND=rerankers

backend/README.md

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

backend/backend.proto

@@ -154,6 +154,10 @@ 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
@@ -164,6 +168,7 @@ 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 {
@@ -242,7 +247,7 @@ message ModelOptions {
 
   string Type = 49;
 
-  bool FlashAttention = 56;
+  string FlashAttention = 56;
   bool NoKVOffload = 57;
 
   string ModelPath = 59;
@@ -276,6 +281,7 @@ message TranscriptRequest {
   string language = 3;
   uint32 threads = 4;
   bool translate = 5;
+  bool diarize = 6;
 }
 
 message TranscriptResult {
@@ -305,19 +311,24 @@ message GenerateImageRequest {
   // Diffusers
   string EnableParameters = 10;
   int32 CLIPSkip = 11;
+
+  // Reference images for models that support them (e.g., Flux Kontext)
+  repeated string ref_images = 12;
 }
 
 message GenerateVideoRequest {
   string prompt = 1;
-  string start_image = 2;  // Path or base64 encoded image for the start frame
-  string end_image = 3;    // Path or base64 encoded image for the end frame
-  int32 width = 4;
-  int32 height = 5;
-  int32 num_frames = 6;    // Number of frames to generate
-  int32 fps = 7;          // Frames per second
-  int32 seed = 8;
-  float cfg_scale = 9;    // Classifier-free guidance scale
-  string dst = 10;        // Output path for the generated video
+  string negative_prompt = 2;  // Negative prompt for video generation
+  string start_image = 3;  // Path or base64 encoded image for the start frame
+  string end_image = 4;    // Path or base64 encoded image for the end frame
+  int32 width = 5;
+  int32 height = 6;
+  int32 num_frames = 7;    // Number of frames to generate
+  int32 fps = 8;          // Frames per second
+  int32 seed = 9;
+  float cfg_scale = 10;    // Classifier-free guidance scale
+  int32 step = 11;         // Number of inference steps
+  string dst = 12;        // Output path for the generated video
 }
 
 message TTSRequest {
@@ -376,6 +387,11 @@ 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 {

backend/cpp/llama-cpp/Makefile

@@ -1,5 +1,5 @@
 
-LLAMA_VERSION?=bf78f5439ee8e82e367674043303ebf8e92b4805
+LLAMA_VERSION?=10e9780154365b191fb43ca4830659ef12def80f
 LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
 
 CMAKE_ARGS?=
@@ -14,7 +14,7 @@ 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
+	CMAKE_ARGS+=-DGGML_NATIVE=OFF -DLLAMA_OPENSSL=OFF
 endif
 # If build type is cublas, then we set -DGGML_CUDA=ON to CMAKE_ARGS automatically
 ifeq ($(BUILD_TYPE),cublas)
@@ -26,16 +26,14 @@ else ifeq ($(BUILD_TYPE),openblas)
 # If build type is clblas (openCL) we set -DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
 else ifeq ($(BUILD_TYPE),clblas)
 	CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
-# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++ 
+# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
 else ifeq ($(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
-#	GPU_TARGETS ?= gfx803,gfx900,gfx906,gfx908,gfx90a,gfx942,gfx1010,gfx1030,gfx1032,gfx1100,gfx1101,gfx1102
-#	AMDGPU_TARGETS ?= "$(GPU_TARGETS)"
-	CMAKE_ARGS+=-DGGML_HIP=ON
-#	CMAKE_ARGS+=-DGGML_HIP=ON -DAMDGPU_TARGETS="$(AMDGPU_TARGETS)" -DGPU_TARGETS="$(GPU_TARGETS)"
+	AMDGPU_TARGETS?=gfx803,gfx900,gfx906,gfx908,gfx90a,gfx942,gfx1010,gfx1030,gfx1032,gfx1100,gfx1101,gfx1102,gfx1200,gfx1201
+	CMAKE_ARGS+=-DGGML_HIP=ON -DAMDGPU_TARGETS=$(AMDGPU_TARGETS)
 else ifeq ($(BUILD_TYPE),vulkan)
 	CMAKE_ARGS+=-DGGML_VULKAN=1
 else ifeq ($(OS),Darwin)

backend/cpp/llama-cpp/prepare.sh

@@ -14,6 +14,8 @@ 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/
+cp -rfv llama.cpp/tools/server/server-http.cpp llama.cpp/tools/grpc-server/
+cp -rfv llama.cpp/tools/server/server-http.h llama.cpp/tools/grpc-server/
 
 set +e
 if grep -q "grpc-server" llama.cpp/tools/CMakeLists.txt; then

backend/cpp/llama-cpp/run.sh

@@ -42,7 +42,8 @@ fi
  
 # Extend ld library path with the dir where this script is located/lib
 if [ "$(uname)" == "Darwin" ]; then
-	DYLD_FALLBACK_LIBRARY_PATH=$CURDIR/lib:$DYLD_FALLBACK_LIBRARY_PATH
+	export DYLD_LIBRARY_PATH=$CURDIR/lib:$DYLD_LIBRARY_PATH
+	#export DYLD_FALLBACK_LIBRARY_PATH=$CURDIR/lib:$DYLD_FALLBACK_LIBRARY_PATH
 else
 	export LD_LIBRARY_PATH=$CURDIR/lib:$LD_LIBRARY_PATH
 fi
@@ -57,5 +58,5 @@ fi
 echo "Using binary: $BINARY"
 exec $CURDIR/$BINARY "$@"
 
-# In case we fail execing, just run fallback
+# We should never reach this point, however just in case we do, run fallback
 exec $CURDIR/llama-cpp-fallback "$@"

backend/go/stablediffusion-ggml/.gitignore

@@ -0,0 +1,6 @@
+package/
+sources/
+.cache/
+build/
+libgosd.so
+stablediffusion-ggml

backend/go/stablediffusion-ggml/CMakeLists.txt

@@ -0,0 +1,20 @@
+cmake_minimum_required(VERSION 3.12)
+project(gosd LANGUAGES C CXX)
+set(CMAKE_POSITION_INDEPENDENT_CODE ON)
+
+add_subdirectory(./sources/stablediffusion-ggml.cpp)
+
+add_library(gosd MODULE gosd.cpp)
+target_link_libraries(gosd PRIVATE stable-diffusion ggml)
+
+if(CMAKE_CXX_COMPILER_ID MATCHES "GNU" AND CMAKE_CXX_COMPILER_VERSION VERSION_LESS 9.0)
+    target_link_libraries(gosd PRIVATE stdc++fs)
+endif()
+
+target_include_directories(gosd PUBLIC
+    stable-diffusion.cpp
+    stable-diffusion.cpp/thirdparty
+)
+
+set_property(TARGET gosd PROPERTY CXX_STANDARD 17)
+set_target_properties(gosd PROPERTIES LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR})

backend/go/stablediffusion-ggml/Makefile

@@ -1,28 +1,16 @@
-INCLUDE_PATH := $(abspath ./)
-LIBRARY_PATH := $(abspath ./)
-
-AR?=ar
 CMAKE_ARGS?=
 BUILD_TYPE?=
 NATIVE?=false
-CUDA_LIBPATH?=/usr/local/cuda/lib64/
-ONEAPI_VARS?=/opt/intel/oneapi/setvars.sh
-# keep standard at C11 and C++11
-CXXFLAGS = -I. -I$(INCLUDE_PATH)/sources/stablediffusion-ggml.cpp/thirdparty -I$(INCLUDE_PATH)/sources/stablediffusion-ggml.cpp/ggml/include -I$(INCLUDE_PATH)/sources/stablediffusion-ggml.cpp -O3 -DNDEBUG -std=c++17 -fPIC
 
 GOCMD?=go
-CGO_LDFLAGS?=
-# Avoid parent make file overwriting CGO_LDFLAGS which is needed for hipblas
-CGO_LDFLAGS_SYCL=
 GO_TAGS?=
-LD_FLAGS?=
+JOBS?=$(shell nproc --ignore=1)
 
 # stablediffusion.cpp (ggml)
 STABLEDIFFUSION_GGML_REPO?=https://github.com/leejet/stable-diffusion.cpp
-STABLEDIFFUSION_GGML_VERSION?=eed97a5e1d054f9c1e7ac01982ae480411d4157e
+STABLEDIFFUSION_GGML_VERSION?=0ebe6fe118f125665939b27c89f34ed38716bff8
 
-# Disable Shared libs as we are linking on static gRPC and we can't mix shared and static
-CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
+CMAKE_ARGS+=-DGGML_MAX_NAME=128
 
 ifeq ($(NATIVE),false)
 	CMAKE_ARGS+=-DGGML_NATIVE=OFF
@@ -31,7 +19,6 @@ endif
 # If build type is cublas, then we set -DGGML_CUDA=ON to CMAKE_ARGS automatically
 ifeq ($(BUILD_TYPE),cublas)
 	CMAKE_ARGS+=-DSD_CUDA=ON -DGGML_CUDA=ON
-	CGO_LDFLAGS+=-lcublas -lcudart -L$(CUDA_LIBPATH) -L$(CUDA_LIBPATH)/stubs/ -lcuda
 # If build type is openblas then we set -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
 # to CMAKE_ARGS automatically
 else ifeq ($(BUILD_TYPE),openblas)
@@ -42,18 +29,14 @@ else ifeq ($(BUILD_TYPE),clblas)
 # If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
 else ifeq ($(BUILD_TYPE),hipblas)
 	CMAKE_ARGS+=-DSD_HIPBLAS=ON -DGGML_HIPBLAS=ON
-# If it's OSX, DO NOT embed the metal library - -DGGML_METAL_EMBED_LIBRARY=ON requires further investigation
-# But if it's OSX without metal, disable it here
 else ifeq ($(BUILD_TYPE),vulkan)
 	CMAKE_ARGS+=-DSD_VULKAN=ON -DGGML_VULKAN=ON
-	CGO_LDFLAGS+=-lvulkan
 else ifeq ($(OS),Darwin)
 	ifneq ($(BUILD_TYPE),metal)
 		CMAKE_ARGS+=-DSD_METAL=OFF -DGGML_METAL=OFF
 	else
 		CMAKE_ARGS+=-DSD_METAL=ON -DGGML_METAL=ON
 		CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=ON
-		TARGET+=--target ggml-metal
 	endif
 endif
 
@@ -63,12 +46,6 @@ ifeq ($(BUILD_TYPE),sycl_f16)
 		-DCMAKE_CXX_COMPILER=icpx \
 		-DSD_SYCL=ON \
 		-DGGML_SYCL_F16=ON
-	export CC=icx
-	export CXX=icpx
-	CGO_LDFLAGS_SYCL += -fsycl -L${DNNLROOT}/lib -ldnnl ${MKLROOT}/lib/intel64/libmkl_sycl.a -fiopenmp -fopenmp-targets=spir64 -lOpenCL
-	CGO_LDFLAGS_SYCL += $(shell pkg-config --libs mkl-static-lp64-gomp)
-	CGO_CXXFLAGS += -fiopenmp -fopenmp-targets=spir64
-	CGO_CXXFLAGS += $(shell pkg-config --cflags mkl-static-lp64-gomp )
 endif
 
 ifeq ($(BUILD_TYPE),sycl_f32)
@@ -76,78 +53,29 @@ ifeq ($(BUILD_TYPE),sycl_f32)
 		-DCMAKE_C_COMPILER=icx \
 		-DCMAKE_CXX_COMPILER=icpx \
 		-DSD_SYCL=ON
-	export CC=icx
-	export CXX=icpx
-	CGO_LDFLAGS_SYCL += -fsycl -L${DNNLROOT}/lib -ldnnl ${MKLROOT}/lib/intel64/libmkl_sycl.a -fiopenmp -fopenmp-targets=spir64 -lOpenCL
-	CGO_LDFLAGS_SYCL += $(shell pkg-config --libs mkl-static-lp64-gomp)
-	CGO_CXXFLAGS += -fiopenmp -fopenmp-targets=spir64
-	CGO_CXXFLAGS += $(shell pkg-config --cflags mkl-static-lp64-gomp )
 endif
 
-# warnings
-# CXXFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function
-
-# Find all .a archives in ARCHIVE_DIR
-# (ggml can have different backends cpu, cuda, etc., each backend generates a .a archive)
-GGML_ARCHIVE_DIR := build/ggml/src/
-ALL_ARCHIVES := $(shell find $(GGML_ARCHIVE_DIR) -type f -name '*.a')
-ALL_OBJS := $(shell find $(GGML_ARCHIVE_DIR) -type f -name '*.o')
-
-# Name of the single merged library
-COMBINED_LIB := libggmlall.a
-
-# Instead of using the archives generated by GGML, use the object files directly to avoid overwriting objects with the same base name
-$(COMBINED_LIB): $(ALL_ARCHIVES)
-	@echo "Merging all .o into $(COMBINED_LIB): $(ALL_OBJS)"
-	rm -f $@
-	ar -qc $@ $(ALL_OBJS)
-	# Ensure we have a proper index
-	ranlib $@
-
-build/libstable-diffusion.a:
-	@echo "Building SD with $(BUILD_TYPE) build type and $(CMAKE_ARGS)"
-ifneq (,$(findstring sycl,$(BUILD_TYPE)))
-	+bash -c "source $(ONEAPI_VARS); \
-	mkdir -p build && \
-	cd build && \
-	cmake $(CMAKE_ARGS) ../sources/stablediffusion-ggml.cpp && \
-	cmake --build . --config Release"
-else
-	mkdir -p build && \
-	cd build && \
-	cmake $(CMAKE_ARGS) ../sources/stablediffusion-ggml.cpp && \
-	cmake --build . --config Release
-endif
-	$(MAKE) $(COMBINED_LIB)
-
-gosd.o:
-ifneq (,$(findstring sycl,$(BUILD_TYPE)))
-	+bash -c "source $(ONEAPI_VARS); \
-	$(CXX) $(CXXFLAGS) gosd.cpp -o gosd.o -c"
-else
-	$(CXX) $(CXXFLAGS) gosd.cpp -o gosd.o -c
-endif
-
-## stablediffusion (ggml)
 sources/stablediffusion-ggml.cpp:
 	git clone --recursive $(STABLEDIFFUSION_GGML_REPO) sources/stablediffusion-ggml.cpp && \
 	cd sources/stablediffusion-ggml.cpp && \
 	git checkout $(STABLEDIFFUSION_GGML_VERSION) && \
 	git submodule update --init --recursive --depth 1 --single-branch
 
-libsd.a: sources/stablediffusion-ggml.cpp build/libstable-diffusion.a gosd.o
-	cp $(INCLUDE_PATH)/build/libstable-diffusion.a ./libsd.a
-	$(AR) rcs libsd.a gosd.o
+libgosd.so: sources/stablediffusion-ggml.cpp CMakeLists.txt gosd.cpp gosd.h
+	mkdir -p build && \
+	cd build && \
+	cmake .. $(CMAKE_ARGS) && \
+	cmake --build . --config Release -j$(JOBS) && \
+	cd .. && \
+	mv build/libgosd.so ./
 
-stablediffusion-ggml: libsd.a
-	CGO_LDFLAGS="$(CGO_LDFLAGS) $(CGO_LDFLAGS_SYCL)" C_INCLUDE_PATH="$(INCLUDE_PATH)" LIBRARY_PATH="$(LIBRARY_PATH)" \
-	CC="$(CC)" CXX="$(CXX)" CGO_CXXFLAGS="$(CGO_CXXFLAGS)" \
-	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o stablediffusion-ggml ./
+stablediffusion-ggml: main.go gosd.go libgosd.so
+	CGO_ENABLED=0 $(GOCMD) build -tags "$(GO_TAGS)" -o stablediffusion-ggml ./
 
-package:
+package: stablediffusion-ggml
 	bash package.sh
 
-build: stablediffusion-ggml package
+build: package
 
 clean:
-	rm -rf gosd.o libsd.a build $(COMBINED_LIB)
+	rm -rf libgosd.so build stablediffusion-ggml package sources

backend/go/stablediffusion-ggml/gosd.cpp

@@ -1,16 +1,14 @@
+#include <cstdint>
+#define GGML_MAX_NAME 128
+
 #include <stdio.h>
 #include <string.h>
 #include <time.h>
-#include <iostream>
-#include <random>
 #include <string>
 #include <vector>
+#include <filesystem>
 #include "gosd.h"
 
-// #include "preprocessing.hpp"
-#include "flux.hpp"
-#include "stable-diffusion.h"
-
 #define STB_IMAGE_IMPLEMENTATION
 #define STB_IMAGE_STATIC
 #include "stb_image.h"
@@ -25,7 +23,7 @@
 
 // Names of the sampler method, same order as enum sample_method in stable-diffusion.h
 const char* sample_method_str[] = {
-    "euler_a",
+    "default",
     "euler",
     "heun",
     "dpm2",
@@ -37,24 +35,32 @@ 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* schedule_str[] = {
+const char* schedulers[] = {
     "default",
     "discrete",
     "karras",
     "exponential",
     "ays",
     "gits",
+    "smoothstep",
 };
 
+static_assert(std::size(schedulers) == SCHEDULE_COUNT, "schedulers mismatch");
+
 sd_ctx_t* sd_c;
+// Moved from the context (load time) to generation time params
+scheduler_t scheduler = scheduler_t::DEFAULT;
 
 sample_method_t sample_method;
 
 // Copied from the upstream CLI
-void sd_log_cb(enum sd_log_level_t level, const char* log, void* data) {
+static void sd_log_cb(enum sd_log_level_t level, const char* log, void* data) {
     //SDParams* params = (SDParams*)data;
     const char* level_str;
 
@@ -85,31 +91,33 @@ void sd_log_cb(enum sd_log_level_t level, const char* log, void* data) {
     fflush(stderr);
 }
 
-int load_model(char *model, char* options[], int threads, int diff) {
-    fprintf (stderr, "Loading model!\n");
+int load_model(const char *model, char *model_path, char* options[], int threads, int diff) {
+    fprintf (stderr, "Loading model: %p=%s\n", model, model);
 
     sd_set_log_callback(sd_log_cb, NULL);
 
-    char *stableDiffusionModel = "";
+    const char *stableDiffusionModel = "";
     if (diff == 1 ) {
         stableDiffusionModel = model;
         model = "";
     }
 
     // decode options. Options are in form optname:optvale, or if booleans only optname.
-    char *clip_l_path  = "";
-    char *clip_g_path  = "";
-    char *t5xxl_path  = "";
-    char *vae_path  = "";
-    char *scheduler = "";
-    char *sampler = "";
+    const char *clip_l_path  = "";
+    const char *clip_g_path  = "";
+    const char *t5xxl_path  = "";
+    const char *vae_path  = "";
+    const char *scheduler_str = "";
+    const char *sampler = "";
+    char *lora_dir = model_path;
+    bool lora_dir_allocated = false;
 
-    fprintf(stderr, "parsing options\n");
+    fprintf(stderr, "parsing options: %p\n", options);
 
     // If options is not NULL, parse options
     for (int i = 0; options[i] != NULL; i++) {
-        char *optname = strtok(options[i], ":");
-        char *optval = strtok(NULL, ":");
+        const char *optname = strtok(options[i], ":");
+        const char *optval = strtok(NULL, ":");
         if (optval == NULL) {
             optval = "true";
         }
@@ -127,11 +135,26 @@ int load_model(char *model, char* options[], int threads, int diff) {
             vae_path = optval;
         }
         if (!strcmp(optname, "scheduler")) {
-            scheduler = optval;
+            scheduler_str = optval;
         }
         if (!strcmp(optname, "sampler")) {
             sampler = optval;
         }
+        if (!strcmp(optname, "lora_dir")) {
+            // Path join with model dir
+            if (model_path && strlen(model_path) > 0) {
+                std::filesystem::path model_path_str(model_path);
+                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_allocated = true;
+                fprintf(stderr, "Lora dir resolved to: %s\n", lora_dir);
+            } else {
+                lora_dir = strdup(optval);
+                lora_dir_allocated = true;
+                fprintf(stderr, "No model path provided, using lora dir as-is: %s\n", lora_dir);
+            }
+        }
     }
 
     fprintf(stderr, "parsed options\n");
@@ -145,26 +168,17 @@ int load_model(char *model, char* options[], int threads, int diff) {
     }
     if (sample_method_found == -1) {
         fprintf(stderr, "Invalid sample method, default to EULER_A!\n");
-        sample_method_found = EULER_A;
+        sample_method_found = sample_method_t::SAMPLE_METHOD_DEFAULT;
     }
     sample_method = (sample_method_t)sample_method_found;
 
-    int schedule_found            = -1;
     for (int d = 0; d < SCHEDULE_COUNT; d++) {
-        if (!strcmp(scheduler, schedule_str[d])) {
-            schedule_found = d;
-                fprintf (stderr, "Found scheduler: %s\n", scheduler);
-
+        if (!strcmp(scheduler_str, schedulers[d])) {
+            scheduler = (scheduler_t)d;
+            fprintf (stderr, "Found scheduler: %s\n", scheduler_str);
         }
     }
 
-    if (schedule_found == -1) {
-        fprintf (stderr, "Invalid scheduler! using DEFAULT\n");
-        schedule_found = DEFAULT;
-    }
-
-    schedule_t schedule = (schedule_t)schedule_found;
-
     fprintf (stderr, "Creating context\n");
     sd_ctx_params_t ctx_params;
     sd_ctx_params_init(&ctx_params);
@@ -176,29 +190,77 @@ int load_model(char *model, char* options[], int threads, int diff) {
     ctx_params.vae_path = vae_path;
     ctx_params.taesd_path = "";
     ctx_params.control_net_path = "";
-    ctx_params.lora_model_dir = "";
+    ctx_params.lora_model_dir = lora_dir;
     ctx_params.embedding_dir = "";
-    ctx_params.stacked_id_embed_dir = "";
     ctx_params.vae_decode_only = false;
-    ctx_params.vae_tiling = false;
     ctx_params.free_params_immediately = false;
     ctx_params.n_threads = threads;
     ctx_params.rng_type = STD_DEFAULT_RNG;
-    ctx_params.schedule = schedule;
     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;
 }
 
-int gen_image(char *text, char *negativeText, int width, int height, int steps, int seed , char *dst, float cfg_scale) {
+void sd_tiling_params_set_enabled(sd_tiling_params_t *params, bool enabled) {
+    params->enabled = enabled;
+}
+
+void sd_tiling_params_set_tile_sizes(sd_tiling_params_t *params, int tile_size_x, int tile_size_y) {
+    params->tile_size_x = tile_size_x;
+    params->tile_size_y = tile_size_y;
+}
+
+void sd_tiling_params_set_rel_sizes(sd_tiling_params_t *params, float rel_size_x, float rel_size_y) {
+    params->rel_size_x = rel_size_x;
+    params->rel_size_y = rel_size_y;
+}
+
+void sd_tiling_params_set_target_overlap(sd_tiling_params_t *params, float target_overlap) {
+    params->target_overlap = target_overlap;
+}
+
+sd_tiling_params_t* sd_img_gen_params_get_vae_tiling_params(sd_img_gen_params_t *params) {
+    return &params->vae_tiling_params;
+}
+
+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);
+    return params;
+}
+
+void sd_img_gen_params_set_prompts(sd_img_gen_params_t *params, const char *prompt, const char *negative_prompt) {
+    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) {
+    params->width = width;
+    params->height = height;
+}
+
+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) {
 
     sd_image_t* results;
 
@@ -206,30 +268,199 @@ int gen_image(char *text, char *negativeText, int width, int height, int steps,
 
     fprintf (stderr, "Generating image\n");
 
-    sd_img_gen_params_t p;
-    sd_img_gen_params_init(&p);
+    p->sample_params.guidance.txt_cfg = cfg_scale;
+    p->sample_params.guidance.slg.layers = skip_layers.data();
+    p->sample_params.guidance.slg.layer_count = skip_layers.size();
+    p->sample_params.sample_method = sample_method;
+    p->sample_params.sample_steps = steps;
+    p->sample_params.scheduler = scheduler;
 
-    p.prompt = text;
-    p.negative_prompt = negativeText;
-    p.guidance.txt_cfg = cfg_scale;
-    p.guidance.slg.layers = skip_layers.data();
-    p.guidance.slg.layer_count = skip_layers.size();
-    p.width = width;
-    p.height = height;
-    p.sample_method = sample_method;
-    p.sample_steps = steps;
-    p.seed = seed;
-    p.input_id_images_path = "";
+    int width = p->width;
+    int height = p->height;
 
-    results = generate_image(sd_c, &p);
+    // Handle input image for img2img
+    bool has_input_image = (src_image != NULL && strlen(src_image) > 0);
+    bool has_mask_image = (mask_image != NULL && strlen(mask_image) > 0);
+
+    uint8_t* input_image_buffer = NULL;
+    uint8_t* mask_image_buffer = NULL;
+    std::vector<uint8_t> default_mask_image_vec;
+
+    if (has_input_image) {
+        fprintf(stderr, "Loading input image: %s\n", src_image);
+
+        int c = 0;
+        int img_width = 0;
+        int img_height = 0;
+        input_image_buffer = stbi_load(src_image, &img_width, &img_height, &c, 3);
+        if (input_image_buffer == NULL) {
+            fprintf(stderr, "Failed to load input image from '%s'\n", src_image);
+            return 1;
+        }
+        if (c < 3) {
+            fprintf(stderr, "Input image must have at least 3 channels, got %d\n", c);
+            free(input_image_buffer);
+            return 1;
+        }
+
+        // Resize input image if dimensions don't match
+        if (img_width != width || img_height != height) {
+            fprintf(stderr, "Resizing input image from %dx%d to %dx%d\n", img_width, img_height, width, height);
+
+            uint8_t* resized_image_buffer = (uint8_t*)malloc(height * width * 3);
+            if (resized_image_buffer == NULL) {
+                fprintf(stderr, "Failed to allocate memory for resized image\n");
+                free(input_image_buffer);
+                return 1;
+            }
+
+            stbir_resize(input_image_buffer, img_width, img_height, 0,
+                         resized_image_buffer, width, height, 0, STBIR_TYPE_UINT8,
+                         3, STBIR_ALPHA_CHANNEL_NONE, 0,
+                         STBIR_EDGE_CLAMP, STBIR_EDGE_CLAMP,
+                         STBIR_FILTER_BOX, STBIR_FILTER_BOX,
+                         STBIR_COLORSPACE_SRGB, nullptr);
+
+            free(input_image_buffer);
+            input_image_buffer = resized_image_buffer;
+        }
+
+        p->init_image = {(uint32_t)width, (uint32_t)height, 3, input_image_buffer};
+        p->strength = strength;
+        fprintf(stderr, "Using img2img with strength: %.2f\n", strength);
+    } else {
+        // No input image, use empty image for text-to-image
+        p->init_image = {(uint32_t)width, (uint32_t)height, 3, NULL};
+        p->strength = 0.0f;
+    }
+
+    // Handle mask image for inpainting
+    if (has_mask_image) {
+        fprintf(stderr, "Loading mask image: %s\n", mask_image);
+
+        int c = 0;
+        int mask_width = 0;
+        int mask_height = 0;
+        mask_image_buffer = stbi_load(mask_image, &mask_width, &mask_height, &c, 1);
+        if (mask_image_buffer == NULL) {
+            fprintf(stderr, "Failed to load mask image from '%s'\n", mask_image);
+            if (input_image_buffer) free(input_image_buffer);
+            return 1;
+        }
+
+        // Resize mask if dimensions don't match
+        if (mask_width != width || mask_height != height) {
+            fprintf(stderr, "Resizing mask image from %dx%d to %dx%d\n", mask_width, mask_height, width, height);
+
+            uint8_t* resized_mask_buffer = (uint8_t*)malloc(height * width);
+            if (resized_mask_buffer == NULL) {
+                fprintf(stderr, "Failed to allocate memory for resized mask\n");
+                free(mask_image_buffer);
+                if (input_image_buffer) free(input_image_buffer);
+                return 1;
+            }
+
+            stbir_resize(mask_image_buffer, mask_width, mask_height, 0,
+                         resized_mask_buffer, width, height, 0, STBIR_TYPE_UINT8,
+                         1, STBIR_ALPHA_CHANNEL_NONE, 0,
+                         STBIR_EDGE_CLAMP, STBIR_EDGE_CLAMP,
+                         STBIR_FILTER_BOX, STBIR_FILTER_BOX,
+                         STBIR_COLORSPACE_SRGB, nullptr);
+
+            free(mask_image_buffer);
+            mask_image_buffer = resized_mask_buffer;
+        }
+
+        p->mask_image = {(uint32_t)width, (uint32_t)height, 1, mask_image_buffer};
+        fprintf(stderr, "Using inpainting with mask\n");
+    } else {
+        // No mask image, create default full mask
+        default_mask_image_vec.resize(width * height, 255);
+        p->mask_image = {(uint32_t)width, (uint32_t)height, 1, default_mask_image_vec.data()};
+    }
+
+    // Handle reference images
+    std::vector<sd_image_t> ref_images_vec;
+    std::vector<uint8_t*> ref_image_buffers;
+
+    if (ref_images_count > 0 && ref_images != NULL) {
+        fprintf(stderr, "Loading %d reference images\n", ref_images_count);
+
+        for (int i = 0; i < ref_images_count; i++) {
+            if (ref_images[i] == NULL || strlen(ref_images[i]) == 0) {
+                continue;
+            }
+
+            fprintf(stderr, "Loading reference image %d: %s\n", i + 1, ref_images[i]);
+
+            int c = 0;
+            int ref_width = 0;
+            int ref_height = 0;
+            uint8_t* ref_image_buffer = stbi_load(ref_images[i], &ref_width, &ref_height, &c, 3);
+            if (ref_image_buffer == NULL) {
+                fprintf(stderr, "Failed to load reference image from '%s'\n", ref_images[i]);
+                continue;
+            }
+            if (c < 3) {
+                fprintf(stderr, "Reference image must have at least 3 channels, got %d\n", c);
+                free(ref_image_buffer);
+                continue;
+            }
+
+            // Resize reference image if dimensions don't match
+            if (ref_width != width || ref_height != height) {
+                fprintf(stderr, "Resizing reference image from %dx%d to %dx%d\n", ref_width, ref_height, width, height);
+
+                uint8_t* resized_ref_buffer = (uint8_t*)malloc(height * width * 3);
+                if (resized_ref_buffer == NULL) {
+                    fprintf(stderr, "Failed to allocate memory for resized reference image\n");
+                    free(ref_image_buffer);
+                    continue;
+                }
+
+                stbir_resize(ref_image_buffer, ref_width, ref_height, 0,
+                             resized_ref_buffer, width, height, 0, STBIR_TYPE_UINT8,
+                             3, STBIR_ALPHA_CHANNEL_NONE, 0,
+                             STBIR_EDGE_CLAMP, STBIR_EDGE_CLAMP,
+                             STBIR_FILTER_BOX, STBIR_FILTER_BOX,
+                             STBIR_COLORSPACE_SRGB, nullptr);
+
+                free(ref_image_buffer);
+                ref_image_buffer = resized_ref_buffer;
+            }
+
+            ref_image_buffers.push_back(ref_image_buffer);
+            ref_images_vec.push_back({(uint32_t)width, (uint32_t)height, 3, ref_image_buffer});
+        }
+
+        if (!ref_images_vec.empty()) {
+            p->ref_images = ref_images_vec.data();
+            p->ref_images_count = ref_images_vec.size();
+            fprintf(stderr, "Using %zu reference images\n", ref_images_vec.size());
+        }
+    }
+
+    results = generate_image(sd_c, p);
+
+    std::free(p);
 
     if (results == NULL) {
         fprintf (stderr, "NO results\n");
+        if (input_image_buffer) free(input_image_buffer);
+        if (mask_image_buffer) free(mask_image_buffer);
+        for (auto buffer : ref_image_buffers) {
+            if (buffer) free(buffer);
+        }
         return 1;
     }
 
     if (results[0].data == NULL) {
         fprintf (stderr, "Results with no data\n");
+        if (input_image_buffer) free(input_image_buffer);
+        if (mask_image_buffer) free(mask_image_buffer);
+        for (auto buffer : ref_image_buffers) {
+            if (buffer) free(buffer);
+        }
         return 1;
     }
 
@@ -245,17 +476,21 @@ int gen_image(char *text, char *negativeText, int width, int height, int steps,
                        results[0].data, 0, NULL);
     fprintf (stderr, "Saved resulting image to '%s'\n", dst);
 
-    // TODO: free results. Why does it crash?
-
+    // Clean up
     free(results[0].data);
     results[0].data = NULL;
     free(results);
-    fprintf (stderr, "gen_image is done", dst);
+    if (input_image_buffer) free(input_image_buffer);
+    if (mask_image_buffer) free(mask_image_buffer);
+    for (auto buffer : ref_image_buffers) {
+        if (buffer) free(buffer);
+    }
+    fprintf (stderr, "gen_image is done: %s", dst);
 
     return 0;
 }
 
 int unload() {
     free_sd_ctx(sd_c);
+    return 0;
 }
-

backend/go/stablediffusion-ggml/gosd.go

@@ -1,15 +1,10 @@
 package main
 
-// #cgo CXXFLAGS: -I${SRCDIR}/sources/stablediffusion-ggml.cpp/thirdparty -I${SRCDIR}/sources/stablediffusion-ggml.cpp -I${SRCDIR}/sources/stablediffusion-ggml.cpp/ggml/include
-// #cgo LDFLAGS: -L${SRCDIR}/ -lsd -lstdc++ -lm -lggmlall -lgomp
-// #include <gosd.h>
-// #include <stdlib.h>
-import "C"
-
 import (
 	"fmt"
 	"os"
 	"path/filepath"
+	"runtime"
 	"strings"
 	"unsafe"
 
@@ -25,20 +20,45 @@ type SDGGML struct {
 	cfgScale     float32
 }
 
+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 []string, refImagesCount int) int
+
+	TilingParamsSetEnabled       func(params uintptr, enabled bool)
+	TilingParamsSetTileSizes     func(params uintptr, tileSizeX int, tileSizeY int)
+	TilingParamsSetRelSizes      func(params uintptr, relSizeX float32, relSizeY float32)
+	TilingParamsSetTargetOverlap func(params uintptr, targetOverlap float32)
+
+	ImgGenParamsNew                func() uintptr
+	ImgGenParamsSetPrompts         func(params uintptr, prompt string, negativePrompt string)
+	ImgGenParamsSetDimensions      func(params uintptr, width int, height int)
+	ImgGenParamsSetSeed            func(params uintptr, seed int64)
+	ImgGenParamsGetVaeTilingParams func(params uintptr) uintptr
+)
+
+// Copied from Purego internal/strings
+// TODO: We should upstream sending []string
+func hasSuffix(s, suffix string) bool {
+	return len(s) >= len(suffix) && s[len(s)-len(suffix):] == suffix
+}
+
+func CString(name string) *byte {
+	if hasSuffix(name, "\x00") {
+		return &(*(*[]byte)(unsafe.Pointer(&name)))[0]
+	}
+	b := make([]byte, len(name)+1)
+	copy(b, name)
+	return &b[0]
+}
+
 func (sd *SDGGML) Load(opts *pb.ModelOptions) error {
 
 	sd.threads = int(opts.Threads)
 
-	modelFile := C.CString(opts.ModelFile)
-	defer C.free(unsafe.Pointer(modelFile))
+	modelPath := opts.ModelPath
 
-	var options **C.char
-	// prepare the options array to pass to C
-
-	size := C.size_t(unsafe.Sizeof((*C.char)(nil)))
-	length := C.size_t(len(opts.Options))
-	options = (**C.char)(C.malloc((length + 1) * size))
-	view := (*[1 << 30]*C.char)(unsafe.Pointer(options))[0:len(opts.Options) + 1:len(opts.Options) + 1]
+	modelFile := opts.ModelFile
+	modelPathC := modelPath
 
 	var diffusionModel int
 
@@ -63,32 +83,63 @@ func (sd *SDGGML) Load(opts *pb.ModelOptions) error {
 
 	fmt.Fprintf(os.Stderr, "Options: %+v\n", oo)
 
-	for i, x := range oo {
-		view[i] = C.CString(x)
+	// 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
+	options := make([]uintptr, len(oo), len(oo)+1)
+	for i, op := range oo {
+		bytep := CString(op)
+		options[i] = uintptr(unsafe.Pointer(bytep))
+		keepAlive = append(keepAlive, bytep)
 	}
-	view[len(oo)] = nil
 
 	sd.cfgScale = opts.CFGScale
 
-	ret := C.load_model(modelFile, options, C.int(opts.Threads), C.int(diffusionModel))
+	ret := LoadModel(modelFile, modelPathC, options, opts.Threads, diffusionModel)
 	if ret != 0 {
 		return fmt.Errorf("could not load model")
 	}
 
+	runtime.KeepAlive(keepAlive)
+
 	return nil
 }
 
 func (sd *SDGGML) GenerateImage(opts *pb.GenerateImageRequest) error {
-	t := C.CString(opts.PositivePrompt)
-	defer C.free(unsafe.Pointer(t))
+	t := opts.PositivePrompt
+	dst := opts.Dst
+	negative := opts.NegativePrompt
+	srcImage := opts.Src
 
-	dst := C.CString(opts.Dst)
-	defer C.free(unsafe.Pointer(dst))
+	var maskImage string
+	if opts.EnableParameters != "" {
+		if strings.Contains(opts.EnableParameters, "mask:") {
+			parts := strings.Split(opts.EnableParameters, "mask:")
+			if len(parts) > 1 {
+				maskPath := strings.TrimSpace(parts[1])
+				if maskPath != "" {
+					maskImage = maskPath
+				}
+			}
+		}
+	}
 
-	negative := C.CString(opts.NegativePrompt)
-	defer C.free(unsafe.Pointer(negative))
+	refImagesCount := len(opts.RefImages)
+	refImages := make([]string, refImagesCount, refImagesCount+1)
+	copy(refImages, opts.RefImages)
+	*(*uintptr)(unsafe.Add(unsafe.Pointer(&refImages), refImagesCount)) = 0
 
-	ret := C.gen_image(t, negative, C.int(opts.Width), C.int(opts.Height), C.int(opts.Step), C.int(opts.Seed), dst, C.float(sd.cfgScale))
+	// Default strength for img2img (0.75 is a good default)
+	strength := float32(0.75)
+
+	// free'd by GenImage
+	p := ImgGenParamsNew()
+	ImgGenParamsSetPrompts(p, t, negative)
+	ImgGenParamsSetDimensions(p, int(opts.Width), int(opts.Height))
+	ImgGenParamsSetSeed(p, int64(opts.Seed))
+	vaep := ImgGenParamsGetVaeTilingParams(p)
+	TilingParamsSetEnabled(vaep, false)
+
+	ret := GenImage(p, int(opts.Step), dst, sd.cfgScale, srcImage, strength, maskImage, refImages, refImagesCount)
 	if ret != 0 {
 		return fmt.Errorf("inference failed")
 	}

backend/go/stablediffusion-ggml/gosd.h

@@ -1,8 +1,23 @@
+#include <cstdint>
+#include "stable-diffusion.h"
+
 #ifdef __cplusplus
 extern "C" {
 #endif
-int load_model(char *model, char* options[], int threads, int diffusionModel);
-int gen_image(char *text, char *negativeText, int width, int height, int steps, int seed, char *dst, float cfg_scale);
+
+void sd_tiling_params_set_enabled(sd_tiling_params_t *params, bool enabled);
+void sd_tiling_params_set_tile_sizes(sd_tiling_params_t *params, int tile_size_x, int tile_size_y);
+void sd_tiling_params_set_rel_sizes(sd_tiling_params_t *params, float rel_size_x, float rel_size_y);
+void sd_tiling_params_set_target_overlap(sd_tiling_params_t *params, float target_overlap);
+sd_tiling_params_t* sd_img_gen_params_get_vae_tiling_params(sd_img_gen_params_t *params);
+
+sd_img_gen_params_t* sd_img_gen_params_new(void);
+void sd_img_gen_params_set_prompts(sd_img_gen_params_t *params, const char *prompt, const char *negative_prompt);
+void sd_img_gen_params_set_dimensions(sd_img_gen_params_t *params, int width, int height);
+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);
 #ifdef __cplusplus
 }
-#endif
+#endif

backend/go/stablediffusion-ggml/main.go

@@ -1,9 +1,9 @@
 package main
 
-// Note: this is started internally by LocalAI and a server is allocated for each model
 import (
 	"flag"
 
+	"github.com/ebitengine/purego"
 	grpc "github.com/mudler/LocalAI/pkg/grpc"
 )
 
@@ -11,7 +11,36 @@ var (
 	addr = flag.String("addr", "localhost:50051", "the address to connect to")
 )
 
+type LibFuncs struct {
+	FuncPtr any
+	Name    string
+}
+
 func main() {
+	gosd, err := purego.Dlopen("./libgosd.so", purego.RTLD_NOW|purego.RTLD_GLOBAL)
+	if err != nil {
+		panic(err)
+	}
+
+	libFuncs := []LibFuncs{
+		{&LoadModel, "load_model"},
+		{&GenImage, "gen_image"},
+		{&TilingParamsSetEnabled, "sd_tiling_params_set_enabled"},
+		{&TilingParamsSetTileSizes, "sd_tiling_params_set_tile_sizes"},
+		{&TilingParamsSetRelSizes, "sd_tiling_params_set_rel_sizes"},
+		{&TilingParamsSetTargetOverlap, "sd_tiling_params_set_target_overlap"},
+
+		{&ImgGenParamsNew, "sd_img_gen_params_new"},
+		{&ImgGenParamsSetPrompts, "sd_img_gen_params_set_prompts"},
+		{&ImgGenParamsSetDimensions, "sd_img_gen_params_set_dimensions"},
+		{&ImgGenParamsSetSeed, "sd_img_gen_params_set_seed"},
+		{&ImgGenParamsGetVaeTilingParams, "sd_img_gen_params_get_vae_tiling_params"},
+	}
+
+	for _, lf := range libFuncs {
+		purego.RegisterLibFunc(lf.FuncPtr, gosd, lf.Name)
+	}
+
 	flag.Parse()
 
 	if err := grpc.StartServer(*addr, &SDGGML{}); err != nil {

backend/go/stablediffusion-ggml/package.sh

@@ -10,8 +10,9 @@ CURDIR=$(dirname "$(realpath $0)")
 # Create lib directory
 mkdir -p $CURDIR/package/lib
 
-cp -avrf $CURDIR/stablediffusion-ggml $CURDIR/package/
-cp -rfv $CURDIR/run.sh $CURDIR/package/
+cp -avf $CURDIR/libgosd.so $CURDIR/package/
+cp -avf $CURDIR/stablediffusion-ggml $CURDIR/package/
+cp -fv $CURDIR/run.sh $CURDIR/package/
 
 # Detect architecture and copy appropriate libraries
 if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
@@ -42,11 +43,13 @@ elif [ -f "/lib/ld-linux-aarch64.so.1" ]; then
     cp -arfLv /lib/aarch64-linux-gnu/libdl.so.2 $CURDIR/package/lib/libdl.so.2
     cp -arfLv /lib/aarch64-linux-gnu/librt.so.1 $CURDIR/package/lib/librt.so.1
     cp -arfLv /lib/aarch64-linux-gnu/libpthread.so.0 $CURDIR/package/lib/libpthread.so.0
+elif [ $(uname -s) = "Darwin" ]; then
+    echo "Detected Darwin"
 else
     echo "Error: Could not detect architecture"
     exit 1
 fi
 
-echo "Packaging completed successfully" 
+echo "Packaging completed successfully"
 ls -liah $CURDIR/package/
-ls -liah $CURDIR/package/lib/
+ls -liah $CURDIR/package/lib/

backend/go/whisper/.gitignore

@@ -0,0 +1,7 @@
+.cache/
+sources/
+build/
+package/
+whisper
+libgowhisper.so
+

backend/go/whisper/CMakeLists.txt

@@ -0,0 +1,16 @@
+cmake_minimum_required(VERSION 3.12)
+project(gowhisper LANGUAGES C CXX)
+set(CMAKE_POSITION_INDEPENDENT_CODE ON)
+set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
+
+add_subdirectory(./sources/whisper.cpp)
+
+add_library(gowhisper MODULE gowhisper.cpp)
+target_link_libraries(gowhisper PRIVATE whisper ggml)
+
+if(CMAKE_CXX_COMPILER_ID MATCHES "GNU" AND CMAKE_CXX_COMPILER_VERSION VERSION_LESS 9.0)
+    target_link_libraries(gosd PRIVATE stdc++fs)
+endif()
+
+set_property(TARGET gowhisper PROPERTY CXX_STANDARD 17)
+set_target_properties(gowhisper PROPERTIES LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR})

backend/go/whisper/Makefile

@@ -1,110 +1,54 @@
-GOCMD=go
+CMAKE_ARGS?=
+BUILD_TYPE?=
 NATIVE?=false
 
-BUILD_TYPE?=
-CMAKE_ARGS?=
+GOCMD?=go
+GO_TAGS?=
+JOBS?=$(shell nproc --ignore=1)
 
 # whisper.cpp version
 WHISPER_REPO?=https://github.com/ggml-org/whisper.cpp
-WHISPER_CPP_VERSION?=e7bf0294ec9099b5fc21f5ba969805dfb2108cea
+WHISPER_CPP_VERSION?=b12abefa9be2abae39a73fa903322af135024a36
+SO_TARGET?=libgowhisper.so
 
-export WHISPER_CMAKE_ARGS?=-DBUILD_SHARED_LIBS=OFF
-export WHISPER_DIR=$(abspath ./sources/whisper.cpp)
-export WHISPER_INCLUDE_PATH=$(WHISPER_DIR)/include:$(WHISPER_DIR)/ggml/include
-export WHISPER_LIBRARY_PATH=$(WHISPER_DIR)/build/src/:$(WHISPER_DIR)/build/ggml/src
+CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
 
-CGO_LDFLAGS_WHISPER?=
-CGO_LDFLAGS_WHISPER+=-lggml
-CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF -DLLAMA_CURL=OFF
-CUDA_LIBPATH?=/usr/local/cuda/lib64/
-
-ONEAPI_VERSION?=2025.2
-
-# IF native is false, we add -DGGML_NATIVE=OFF to CMAKE_ARGS
-ifeq ($(NATIVE),false)
-	CMAKE_ARGS+=-DGGML_NATIVE=OFF
-	WHISPER_CMAKE_ARGS+=-DGGML_NATIVE=OFF
-endif
-CURRENT_MAKEFILE_DIR := $(dir $(abspath $(lastword $(MAKEFILE_LIST))))
 ifeq ($(NATIVE),false)
 	CMAKE_ARGS+=-DGGML_NATIVE=OFF
 endif
-# If build type is cublas, then we set -DGGML_CUDA=ON to CMAKE_ARGS automatically
+
 ifeq ($(BUILD_TYPE),cublas)
-	CGO_LDFLAGS+=-lcublas -lcudart -L$(CUDA_LIBPATH) -L$(CUDA_LIBPATH)/stubs/ -lcuda
 	CMAKE_ARGS+=-DGGML_CUDA=ON
-	CGO_LDFLAGS_WHISPER+=-lcufft -lggml-cuda
-	export WHISPER_LIBRARY_PATH:=$(WHISPER_LIBRARY_PATH):$(WHISPER_DIR)/build/ggml/src/ggml-cuda/
-# If build type is openblas then we set -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
-# to CMAKE_ARGS automatically
 else ifeq ($(BUILD_TYPE),openblas)
 	CMAKE_ARGS+=-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
-# If build type is clblas (openCL) we set -DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
 else ifeq ($(BUILD_TYPE),clblas)
 	CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
-# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
 else ifeq ($(BUILD_TYPE),hipblas)
-	ROCM_HOME ?= /opt/rocm
-	ROCM_PATH ?= /opt/rocm
-	LD_LIBRARY_PATH ?= /opt/rocm/lib:/opt/rocm/llvm/lib
-	export STABLE_BUILD_TYPE=
-	export CXX=$(ROCM_HOME)/llvm/bin/clang++
-	export CC=$(ROCM_HOME)/llvm/bin/clang
-#	GPU_TARGETS ?= gfx803,gfx900,gfx906,gfx908,gfx90a,gfx942,gfx1010,gfx1030,gfx1032,gfx1100,gfx1101,gfx1102
-#	AMDGPU_TARGETS ?= "$(GPU_TARGETS)"
-	CMAKE_ARGS+=-DGGML_HIP=ON
-	CGO_LDFLAGS += -O3 --rtlib=compiler-rt -unwindlib=libgcc -lhipblas -lrocblas --hip-link -L${ROCM_HOME}/lib/llvm/lib -L$(CURRENT_MAKEFILE_DIR)/sources/whisper.cpp/build/ggml/src/ggml-hip/ -lggml-hip
-#	CMAKE_ARGS+=-DGGML_HIP=ON -DAMDGPU_TARGETS="$(AMDGPU_TARGETS)" -DGPU_TARGETS="$(GPU_TARGETS)"
+	CMAKE_ARGS+=-DGGML_HIPBLAS=ON
 else ifeq ($(BUILD_TYPE),vulkan)
-	CMAKE_ARGS+=-DGGML_VULKAN=1
-	CGO_LDFLAGS_WHISPER+=-lggml-vulkan -lvulkan
-	export WHISPER_LIBRARY_PATH:=$(WHISPER_LIBRARY_PATH):$(WHISPER_DIR)/build/ggml/src/ggml-vulkan/
+	CMAKE_ARGS+=-DGGML_VULKAN=ON
 else ifeq ($(OS),Darwin)
-	ifeq ($(BUILD_TYPE),)
-		BUILD_TYPE=metal
-	endif
 	ifneq ($(BUILD_TYPE),metal)
 		CMAKE_ARGS+=-DGGML_METAL=OFF
-		CGO_LDFLAGS_WHISPER+=-lggml-blas
-		export WHISPER_LIBRARY_PATH:=$(WHISPER_LIBRARY_PATH):$(WHISPER_DIR)/build/ggml/src/ggml-blas
 	else
 		CMAKE_ARGS+=-DGGML_METAL=ON
 		CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=ON
-		CMAKE_ARGS+=-DGGML_METAL_USE_BF16=ON
-		CMAKE_ARGS+=-DGGML_OPENMP=OFF
-		CMAKE_ARGS+=-DWHISPER_BUILD_EXAMPLES=OFF
-		CMAKE_ARGS+=-DWHISPER_BUILD_TESTS=OFF
-		CMAKE_ARGS+=-DWHISPER_BUILD_SERVER=OFF
-		CGO_LDFLAGS += -framework Accelerate
-		CGO_LDFLAGS_WHISPER+=-lggml-metal -lggml-blas
-		export WHISPER_LIBRARY_PATH:=$(WHISPER_LIBRARY_PATH):$(WHISPER_DIR)/build/ggml/src/ggml-metal/:$(WHISPER_DIR)/build/ggml/src/ggml-blas
 	endif
-	TARGET+=--target ggml-metal
-endif
-
-ifneq (,$(findstring sycl,$(BUILD_TYPE)))
-	export CC=icx
-	export CXX=icpx
-	CGO_LDFLAGS_WHISPER += -fsycl -L${DNNLROOT}/lib -rpath ${ONEAPI_ROOT}/${ONEAPI_VERSION}/lib -ldnnl ${MKLROOT}/lib/intel64/libmkl_sycl.a -fiopenmp -fopenmp-targets=spir64 -lOpenCL -lggml-sycl
-	CGO_LDFLAGS_WHISPER += $(shell pkg-config --libs mkl-static-lp64-gomp)
-	CGO_CXXFLAGS_WHISPER += -fiopenmp -fopenmp-targets=spir64
-	CGO_CXXFLAGS_WHISPER += $(shell pkg-config --cflags mkl-static-lp64-gomp )
-	export WHISPER_LIBRARY_PATH:=$(WHISPER_LIBRARY_PATH):$(WHISPER_DIR)/build/ggml/src/ggml-sycl/
-	CMAKE_ARGS+=-DGGML_SYCL=ON \
-		-DCMAKE_C_COMPILER=icx \
-		-DCMAKE_CXX_COMPILER=icpx \
-		-DCMAKE_CXX_FLAGS="-fsycl"
 endif
 
 ifeq ($(BUILD_TYPE),sycl_f16)
-	CMAKE_ARGS+=-DGGML_SYCL_F16=ON
+	CMAKE_ARGS+=-DGGML_SYCL=ON \
+		-DCMAKE_C_COMPILER=icx \
+		-DCMAKE_CXX_COMPILER=icpx \
+		-DGGML_SYCL_F16=ON
 endif
 
-ifneq ($(OS),Darwin)
-	CGO_LDFLAGS_WHISPER+=-lgomp
+ifeq ($(BUILD_TYPE),sycl_f32)
+	CMAKE_ARGS+=-DGGML_SYCL=ON \
+		-DCMAKE_C_COMPILER=icx \
+		-DCMAKE_CXX_COMPILER=icpx
 endif
 
-## whisper
 sources/whisper.cpp:
 	mkdir -p sources/whisper.cpp
 	cd sources/whisper.cpp && \
@@ -114,18 +58,65 @@ sources/whisper.cpp:
 	git checkout $(WHISPER_CPP_VERSION) && \
 	git submodule update --init --recursive --depth 1 --single-branch
 
-sources/whisper.cpp/build/src/libwhisper.a: sources/whisper.cpp
-	cd sources/whisper.cpp && cmake $(CMAKE_ARGS) $(WHISPER_CMAKE_ARGS) . -B ./build
-	cd sources/whisper.cpp/build && cmake --build . --config Release
+# Detect OS
+UNAME_S := $(shell uname -s)
 
-whisper: sources/whisper.cpp sources/whisper.cpp/build/src/libwhisper.a
-	$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp=$(CURDIR)/sources/whisper.cpp
-	$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp/bindings/go=$(CURDIR)/sources/whisper.cpp/bindings/go
-	CGO_LDFLAGS="$(CGO_LDFLAGS) $(CGO_LDFLAGS_WHISPER)" C_INCLUDE_PATH="${WHISPER_INCLUDE_PATH}" LIBRARY_PATH="${WHISPER_LIBRARY_PATH}" LD_LIBRARY_PATH="${WHISPER_LIBRARY_PATH}" \
-	CGO_CXXFLAGS="$(CGO_CXXFLAGS_WHISPER)" \
-	$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o whisper ./
+# Only build CPU variants on Linux
+ifeq ($(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
 
-package:
+whisper: main.go gowhisper.go $(VARIANT_TARGETS)
+	CGO_ENABLED=0 $(GOCMD) build -tags "$(GO_TAGS)" -o whisper ./
+
+package: whisper
 	bash package.sh
 
-build: whisper package
+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

backend/go/whisper/gowhisper.cpp

@@ -0,0 +1,154 @@
+#include "gowhisper.h"
+#include "ggml-backend.h"
+#include "whisper.h"
+#include <vector>
+
+static struct whisper_vad_context *vctx;
+static struct whisper_context *ctx;
+static std::vector<float> flat_segs;
+
+static void ggml_log_cb(enum ggml_log_level level, const char *log,
+                        void *data) {
+  const char *level_str;
+
+  if (!log) {
+    return;
+  }
+
+  switch (level) {
+  case GGML_LOG_LEVEL_DEBUG:
+    level_str = "DEBUG";
+    break;
+  case GGML_LOG_LEVEL_INFO:
+    level_str = "INFO";
+    break;
+  case GGML_LOG_LEVEL_WARN:
+    level_str = "WARN";
+    break;
+  case GGML_LOG_LEVEL_ERROR:
+    level_str = "ERROR";
+    break;
+  default: /* Potential future-proofing */
+    level_str = "?????";
+    break;
+  }
+
+  fprintf(stderr, "[%-5s] ", level_str);
+  fputs(log, stderr);
+  fflush(stderr);
+}
+
+int load_model(const char *const model_path) {
+  whisper_log_set(ggml_log_cb, nullptr);
+  ggml_backend_load_all();
+
+  struct whisper_context_params cparams = whisper_context_default_params();
+
+  ctx = whisper_init_from_file_with_params(model_path, cparams);
+  if (ctx == nullptr) {
+    fprintf(stderr, "error: Also failed to init model as transcriber\n");
+    return 1;
+  }
+
+  return 0;
+}
+
+int load_model_vad(const char *const model_path) {
+  whisper_log_set(ggml_log_cb, nullptr);
+  ggml_backend_load_all();
+
+  struct whisper_vad_context_params vcparams =
+      whisper_vad_default_context_params();
+
+  // XXX: Overridden to false in upstream due to performance?
+  // vcparams.use_gpu = true;
+
+  vctx = whisper_vad_init_from_file_with_params(model_path, vcparams);
+  if (vctx == nullptr) {
+    fprintf(stderr, "error: Failed to init model as VAD\n");
+    return 1;
+  }
+
+  return 0;
+}
+
+int vad(float pcmf32[], size_t pcmf32_len, float **segs_out,
+        size_t *segs_out_len) {
+  if (!whisper_vad_detect_speech(vctx, pcmf32, pcmf32_len)) {
+    fprintf(stderr, "error: failed to detect speech\n");
+    return 1;
+  }
+
+  struct whisper_vad_params params = whisper_vad_default_params();
+  struct whisper_vad_segments *segs =
+      whisper_vad_segments_from_probs(vctx, params);
+  size_t segn = whisper_vad_segments_n_segments(segs);
+
+  // fprintf(stderr, "Got segments %zd\n", segn);
+
+  flat_segs.clear();
+
+  for (int i = 0; i < segn; i++) {
+    flat_segs.push_back(whisper_vad_segments_get_segment_t0(segs, i));
+    flat_segs.push_back(whisper_vad_segments_get_segment_t1(segs, i));
+  }
+
+  // fprintf(stderr, "setting out variables: %p=%p -> %p, %p=%zx -> %zx\n",
+  //         segs_out, *segs_out, flat_segs.data(), segs_out_len, *segs_out_len,
+  //         flat_segs.size());
+  *segs_out = flat_segs.data();
+  *segs_out_len = flat_segs.size();
+
+  // fprintf(stderr, "freeing segs\n");
+  whisper_vad_free_segments(segs);
+
+  // fprintf(stderr, "returning\n");
+  return 0;
+}
+
+int transcribe(uint32_t threads, char *lang, bool translate, bool tdrz,
+               float pcmf32[], size_t pcmf32_len, size_t *segs_out_len) {
+  whisper_full_params wparams =
+      whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
+
+  wparams.n_threads = threads;
+  if (*lang != '\0')
+    wparams.language = lang;
+  else {
+    wparams.language = nullptr;
+  }
+
+  wparams.translate = translate;
+  wparams.debug_mode = true;
+  wparams.print_progress = true;
+  wparams.tdrz_enable = tdrz;
+
+  fprintf(stderr, "info: Enable tdrz: %d\n", tdrz);
+
+  if (whisper_full(ctx, wparams, pcmf32, pcmf32_len)) {
+    fprintf(stderr, "error: transcription failed\n");
+    return 1;
+  }
+
+  *segs_out_len = whisper_full_n_segments(ctx);
+
+  return 0;
+}
+
+const char *get_segment_text(int i) {
+  return whisper_full_get_segment_text(ctx, i);
+}
+
+int64_t get_segment_t0(int i) { return whisper_full_get_segment_t0(ctx, i); }
+
+int64_t get_segment_t1(int i) { return whisper_full_get_segment_t1(ctx, i); }
+
+int n_tokens(int i) { return whisper_full_n_tokens(ctx, i); }
+
+int32_t get_token_id(int i, int j) {
+  return whisper_full_get_token_id(ctx, i, j);
+}
+
+bool get_segment_speaker_turn_next(int i) {
+  return whisper_full_get_segment_speaker_turn_next(ctx, i);
+}

backend/go/whisper/gowhisper.go

@@ -0,0 +1,161 @@
+package main
+
+import (
+	"fmt"
+	"os"
+	"path/filepath"
+	"strings"
+	"unsafe"
+
+	"github.com/go-audio/wav"
+	"github.com/mudler/LocalAI/pkg/grpc/base"
+	pb "github.com/mudler/LocalAI/pkg/grpc/proto"
+	"github.com/mudler/LocalAI/pkg/utils"
+)
+
+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) int
+	CppGetSegmentText            func(i int) string
+	CppGetSegmentStart           func(i int) int64
+	CppGetSegmentEnd             func(i int) int64
+	CppNTokens                   func(i int) int
+	CppGetTokenID                func(i int, j int) int
+	CppGetSegmentSpeakerTurnNext func(i int) bool
+)
+
+type Whisper struct {
+	base.SingleThread
+}
+
+func (w *Whisper) Load(opts *pb.ModelOptions) error {
+	vadOnly := false
+
+	for _, oo := range opts.Options {
+		if oo == "vad_only" {
+			vadOnly = true
+		} else {
+			fmt.Fprintf(os.Stderr, "Unrecognized option: %v\n", oo)
+		}
+	}
+
+	if vadOnly {
+		if ret := CppLoadModelVAD(opts.ModelFile); ret != 0 {
+			return fmt.Errorf("Failed to load Whisper VAD model")
+		}
+
+		return nil
+	}
+
+	if ret := CppLoadModel(opts.ModelFile); ret != 0 {
+		return fmt.Errorf("Failed to load Whisper transcription model")
+	}
+
+	return nil
+}
+
+func (w *Whisper) VAD(req *pb.VADRequest) (pb.VADResponse, error) {
+	audio := req.Audio
+	// We expect 0xdeadbeef to be overwritten and if we see it in a stack trace we know it wasn't
+	segsPtr, segsLen := uintptr(0xdeadbeef), uintptr(0xdeadbeef)
+	segsPtrPtr, segsLenPtr := unsafe.Pointer(&segsPtr), unsafe.Pointer(&segsLen)
+
+	if ret := CppVAD(audio, uintptr(len(audio)), segsPtrPtr, segsLenPtr); ret != 0 {
+		return pb.VADResponse{}, fmt.Errorf("Failed VAD")
+	}
+
+	// Happens when CPP vector has not had any elements pushed to it
+	if segsPtr == 0 {
+		return pb.VADResponse{
+			Segments: []*pb.VADSegment{},
+		}, nil
+	}
+
+	// unsafeptr warning is caused by segsPtr being on the stack and therefor being subject to stack copying AFAICT
+	// however the stack shouldn't have grown between setting segsPtr and now, also the memory pointed to is allocated by C++
+	segs := unsafe.Slice((*float32)(unsafe.Pointer(segsPtr)), segsLen)
+
+	vadSegments := []*pb.VADSegment{}
+	for i := range len(segs) >> 1 {
+		s := segs[2*i] / 100
+		t := segs[2*i+1] / 100
+		vadSegments = append(vadSegments, &pb.VADSegment{
+			Start: s,
+			End:   t,
+		})
+	}
+
+	return pb.VADResponse{
+		Segments: vadSegments,
+	}, nil
+}
+
+func (w *Whisper) AudioTranscription(opts *pb.TranscriptRequest) (pb.TranscriptResult, error) {
+	dir, err := os.MkdirTemp("", "whisper")
+	if err != nil {
+		return pb.TranscriptResult{}, err
+	}
+	defer os.RemoveAll(dir)
+
+	convertedPath := filepath.Join(dir, "converted.wav")
+
+	if err := utils.AudioToWav(opts.Dst, convertedPath); err != nil {
+		return pb.TranscriptResult{}, err
+	}
+
+	// Open samples
+	fh, err := os.Open(convertedPath)
+	if err != nil {
+		return pb.TranscriptResult{}, err
+	}
+	defer fh.Close()
+
+	// Read samples
+	d := wav.NewDecoder(fh)
+	buf, err := d.FullPCMBuffer()
+	if err != nil {
+		return pb.TranscriptResult{}, err
+	}
+
+	data := buf.AsFloat32Buffer().Data
+	segsLen := uintptr(0xdeadbeef)
+	segsLenPtr := unsafe.Pointer(&segsLen)
+
+	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) {
+		s := CppGetSegmentStart(i)
+		t := CppGetSegmentEnd(i)
+		txt := strings.Clone(CppGetSegmentText(i))
+		tokens := make([]int32, CppNTokens(i))
+
+		if opts.Diarize && CppGetSegmentSpeakerTurnNext(i) {
+			txt += " [SPEAKER_TURN]"
+		}
+
+		for j := range tokens {
+			tokens[j] = int32(CppGetTokenID(i, j))
+		}
+		segment := &pb.TranscriptSegment{
+			Id:    int32(i),
+			Text:  txt,
+			Start: s, End: t,
+			Tokens: tokens,
+		}
+
+		segments = append(segments, segment)
+
+		text += " " + strings.TrimSpace(txt)
+	}
+
+	return pb.TranscriptResult{
+		Segments: segments,
+		Text:     strings.TrimSpace(text),
+	}, nil
+}

backend/go/whisper/gowhisper.h

@@ -0,0 +1,17 @@
+#include <cstddef>
+#include <cstdint>
+
+extern "C" {
+int load_model(const char *const model_path);
+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);
+const char *get_segment_text(int i);
+int64_t get_segment_t0(int i);
+int64_t get_segment_t1(int i);
+int n_tokens(int i);
+int32_t get_token_id(int i, int j);
+bool get_segment_speaker_turn_next(int i);
+}

backend/go/whisper/main.go

@@ -1,10 +1,11 @@
 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"
 )
 
@@ -12,7 +13,40 @@ var (
 	addr = flag.String("addr", "localhost:50051", "the address to connect to")
 )
 
+type LibFuncs struct {
+	FuncPtr any
+	Name    string
+}
+
 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)
+	if err != nil {
+		panic(err)
+	}
+
+	libFuncs := []LibFuncs{
+		{&CppLoadModel, "load_model"},
+		{&CppLoadModelVAD, "load_model_vad"},
+		{&CppVAD, "vad"},
+		{&CppTranscribe, "transcribe"},
+		{&CppGetSegmentText, "get_segment_text"},
+		{&CppGetSegmentStart, "get_segment_t0"},
+		{&CppGetSegmentEnd, "get_segment_t1"},
+		{&CppNTokens, "n_tokens"},
+		{&CppGetTokenID, "get_token_id"},
+		{&CppGetSegmentSpeakerTurnNext, "get_segment_speaker_turn_next"},
+	}
+
+	for _, lf := range libFuncs {
+		purego.RegisterLibFunc(lf.FuncPtr, gosd, lf.Name)
+	}
+
 	flag.Parse()
 
 	if err := grpc.StartServer(*addr, &Whisper{}); err != nil {

backend/go/whisper/package.sh

@@ -10,8 +10,9 @@ CURDIR=$(dirname "$(realpath $0)")
 # Create lib directory
 mkdir -p $CURDIR/package/lib
 
-cp -avrf $CURDIR/whisper $CURDIR/package/
-cp -rfv $CURDIR/run.sh $CURDIR/package/
+cp -avf $CURDIR/whisper $CURDIR/package/
+cp -fv $CURDIR/libgowhisper-*.so $CURDIR/package/
+cp -fv $CURDIR/run.sh $CURDIR/package/
 
 # Detect architecture and copy appropriate libraries
 if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
@@ -42,11 +43,13 @@ elif [ -f "/lib/ld-linux-aarch64.so.1" ]; then
     cp -arfLv /lib/aarch64-linux-gnu/libdl.so.2 $CURDIR/package/lib/libdl.so.2
     cp -arfLv /lib/aarch64-linux-gnu/librt.so.1 $CURDIR/package/lib/librt.so.1
     cp -arfLv /lib/aarch64-linux-gnu/libpthread.so.0 $CURDIR/package/lib/libpthread.so.0
+elif [ $(uname -s) = "Darwin" ]; then
+    echo "Detected Darwin"
 else
     echo "Error: Could not detect architecture"
     exit 1
 fi
 
-echo "Packaging completed successfully" 
+echo "Packaging completed successfully"
 ls -liah $CURDIR/package/
-ls -liah $CURDIR/package/lib/
+ls -liah $CURDIR/package/lib/

backend/go/whisper/run.sh

@@ -1,14 +1,52 @@
 #!/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/go/whisper/whisper.go

@@ -1,105 +0,0 @@
-package main
-
-// This is a wrapper to statisfy the GRPC service interface
-// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
-import (
-	"os"
-	"path/filepath"
-
-	"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
-	"github.com/go-audio/wav"
-	"github.com/mudler/LocalAI/pkg/grpc/base"
-	pb "github.com/mudler/LocalAI/pkg/grpc/proto"
-	"github.com/mudler/LocalAI/pkg/utils"
-)
-
-type Whisper struct {
-	base.SingleThread
-	whisper whisper.Model
-}
-
-func (sd *Whisper) Load(opts *pb.ModelOptions) error {
-	// Note: the Model here is a path to a directory containing the model files
-	w, err := whisper.New(opts.ModelFile)
-	sd.whisper = w
-	return err
-}
-
-func (sd *Whisper) AudioTranscription(opts *pb.TranscriptRequest) (pb.TranscriptResult, error) {
-
-	dir, err := os.MkdirTemp("", "whisper")
-	if err != nil {
-		return pb.TranscriptResult{}, err
-	}
-	defer os.RemoveAll(dir)
-
-	convertedPath := filepath.Join(dir, "converted.wav")
-
-	if err := utils.AudioToWav(opts.Dst, convertedPath); err != nil {
-		return pb.TranscriptResult{}, err
-	}
-
-	// Open samples
-	fh, err := os.Open(convertedPath)
-	if err != nil {
-		return pb.TranscriptResult{}, err
-	}
-	defer fh.Close()
-
-	// Read samples
-	d := wav.NewDecoder(fh)
-	buf, err := d.FullPCMBuffer()
-	if err != nil {
-		return pb.TranscriptResult{}, err
-	}
-
-	data := buf.AsFloat32Buffer().Data
-
-	// Process samples
-	context, err := sd.whisper.NewContext()
-	if err != nil {
-		return pb.TranscriptResult{}, err
-
-	}
-
-	context.SetThreads(uint(opts.Threads))
-
-	if opts.Language != "" {
-		context.SetLanguage(opts.Language)
-	} else {
-		context.SetLanguage("auto")
-	}
-
-	if opts.Translate {
-		context.SetTranslate(true)
-	}
-
-	if err := context.Process(data, nil, nil, nil); err != nil {
-		return pb.TranscriptResult{}, err
-	}
-
-	segments := []*pb.TranscriptSegment{}
-	text := ""
-	for {
-		s, err := context.NextSegment()
-		if err != nil {
-			break
-		}
-
-		var tokens []int32
-		for _, t := range s.Tokens {
-			tokens = append(tokens, int32(t.Id))
-		}
-
-		segment := &pb.TranscriptSegment{Id: int32(s.Num), Text: s.Text, Start: int64(s.Start), End: int64(s.End), Tokens: tokens}
-		segments = append(segments, segment)
-
-		text += s.Text
-	}
-
-	return pb.TranscriptResult{
-		Segments: segments,
-		Text:     text,
-	}, nil
-
-}

backend/index.yaml

@@ -45,6 +45,7 @@
     default: "cpu-whisper"
     nvidia: "cuda12-whisper"
     intel: "intel-sycl-f16-whisper"
+    metal: "metal-whisper"
     amd: "rocm-whisper"
     vulkan: "vulkan-whisper"
     nvidia-l4t: "nvidia-l4t-arm64-whisper"
@@ -71,7 +72,7 @@
     # amd: "rocm-stablediffusion-ggml"
     vulkan: "vulkan-stablediffusion-ggml"
     nvidia-l4t: "nvidia-l4t-arm64-stablediffusion-ggml"
-    # metal: "metal-stablediffusion-ggml"
+    metal: "metal-stablediffusion-ggml"
     # darwin-x86: "darwin-x86-stablediffusion-ggml"
 - &rfdetr
   name: "rfdetr"
@@ -127,6 +128,55 @@
     nvidia: "cuda12-vllm"
     amd: "rocm-vllm"
     intel: "intel-vllm"
+- &mlx
+  name: "mlx"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-mlx"
+  icon: https://avatars.githubusercontent.com/u/102832242?s=200&v=4
+  urls:
+    - https://github.com/ml-explore/mlx-lm
+  mirrors:
+    - localai/localai-backends:latest-metal-darwin-arm64-mlx
+  license: MIT
+  description: |
+      Run LLMs with MLX
+  tags:
+    - text-to-text
+    - LLM
+    - MLX
+- &mlx-vlm
+  name: "mlx-vlm"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-mlx-vlm"
+  icon: https://avatars.githubusercontent.com/u/102832242?s=200&v=4
+  urls:
+    - https://github.com/Blaizzy/mlx-vlm
+  mirrors:
+    - localai/localai-backends:latest-metal-darwin-arm64-mlx-vlm
+  license: MIT
+  description: |
+      Run Vision-Language Models with MLX
+  tags:
+    - text-to-text
+    - multimodal
+    - vision-language
+    - LLM
+    - MLX
+- &mlx-audio
+  name: "mlx-audio"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-mlx-audio"
+  icon: https://avatars.githubusercontent.com/u/102832242?s=200&v=4
+  urls:
+    - https://github.com/Blaizzy/mlx-audio
+  mirrors:
+    - localai/localai-backends:latest-metal-darwin-arm64-mlx-audio
+  license: MIT
+  description: |
+      Run Audio Models with MLX
+  tags:
+    - audio-to-text
+    - audio-generation
+    - text-to-audio
+    - LLM
+    - MLX
 - &rerankers
   name: "rerankers"
   alias: "rerankers"
@@ -168,6 +218,9 @@
     nvidia: "cuda12-diffusers"
     intel: "intel-diffusers"
     amd: "rocm-diffusers"
+    nvidia-l4t: "nvidia-l4t-diffusers"
+    metal: "metal-diffusers"
+    default: "cpu-diffusers"
 - &exllama2
   name: "exllama2"
   urls:
@@ -217,6 +270,7 @@
     nvidia: "cuda12-kokoro"
     intel: "intel-kokoro"
     amd: "rocm-kokoro"
+    nvidia-l4t: "nvidia-l4t-kokoro"
 - &coqui
   urls:
     - https://github.com/idiap/coqui-ai-TTS
@@ -294,8 +348,12 @@
   license: MIT
   icon: https://private-user-images.githubusercontent.com/660224/448166653-bd8c5f03-e91d-4ee5-b680-57355da204d1.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3NTAxOTE0MDAsIm5iZiI6MTc1MDE5MTEwMCwicGF0aCI6Ii82NjAyMjQvNDQ4MTY2NjUzLWJkOGM1ZjAzLWU5MWQtNGVlNS1iNjgwLTU3MzU1ZGEyMDRkMS5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjUwNjE3JTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI1MDYxN1QyMDExNDBaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT1hMmI1NGY3OGFiZTlhNGFkNTVlYTY4NTIwMWEzODRiZGE4YzdhNGQ5MGNhNzE3MDYyYTA2NDIxYTkyYzhiODkwJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCJ9.mR9kM9xX0TdzPuSpuspCllHYQiq79dFQ2rtuNvjrl6w
   name: "chatterbox"
+  alias: "chatterbox"
   capabilities:
     nvidia: "cuda12-chatterbox"
+    metal: "metal-chatterbox"
+    default: "cpu-chatterbox"
+    nvidia-l4t: "nvidia-l4t-arm64-chatterbox"
 - &piper
   name: "piper"
   uri: "quay.io/go-skynet/local-ai-backends:latest-piper"
@@ -356,6 +414,101 @@
     - LLM
     - huggingface
   license: MIT
+- &kitten-tts
+  name: "kitten-tts"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-kitten-tts"
+  mirrors:
+    - localai/localai-backends:latest-kitten-tts
+  urls:
+    - https://github.com/KittenML/KittenTTS
+  description: |
+    Kitten TTS is a text-to-speech model that can generate speech from text.
+  tags:
+    - text-to-speech
+    - TTS
+  license: apache-2.0
+- &neutts
+  name: "neutts"
+  urls:
+    - https://github.com/neuphonic/neutts-air
+  description: |
+    NeuTTS Air is the world’s first super-realistic, on-device, TTS speech language model with instant voice cloning. Built off a 0.5B LLM backbone, NeuTTS Air brings natural-sounding speech, real-time performance, built-in security and speaker cloning to your local device - unlocking a new category of embedded voice agents, assistants, toys, and compliance-safe apps.
+  tags:
+    - text-to-speech
+    - TTS
+  license: apache-2.0
+  capabilities:
+    default: "cpu-neutts"
+    nvidia: "cuda12-neutts"
+    amd: "rocm-neutts"
+    nvidia-l4t: "nvidia-l4t-neutts"
+- !!merge <<: *neutts
+  name: "neutts-development"
+  capabilities:
+    default: "cpu-neutts-development"
+    nvidia: "cuda12-neutts-development"
+    amd: "rocm-neutts-development"
+    nvidia-l4t: "nvidia-l4t-neutts-development"
+- !!merge <<: *neutts
+  name: "cpu-neutts"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-neutts"
+  mirrors:
+    - localai/localai-backends:latest-cpu-neutts
+- !!merge <<: *neutts
+  name: "cuda12-neutts"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-neutts"
+  mirrors:
+    - localai/localai-backends:latest-gpu-nvidia-cuda-12-neutts
+- !!merge <<: *neutts
+  name: "rocm-neutts"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-neutts"
+  mirrors:
+    - localai/localai-backends:latest-gpu-rocm-hipblas-neutts
+- !!merge <<: *neutts
+  name: "nvidia-l4t-neutts"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-arm64-neutts"
+  mirrors:
+    - localai/localai-backends:latest-nvidia-l4t-arm64-neutts
+- !!merge <<: *neutts
+  name: "cpu-neutts-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-cpu-neutts"
+  mirrors:
+    - localai/localai-backends:master-cpu-neutts
+- !!merge <<: *neutts
+  name: "cuda12-neutts-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-neutts"
+  mirrors:
+    - localai/localai-backends:master-gpu-nvidia-cuda-12-neutts
+- !!merge <<: *neutts
+  name: "rocm-neutts-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-neutts"
+  mirrors:
+    - localai/localai-backends:master-gpu-rocm-hipblas-neutts
+- !!merge <<: *neutts
+  name: "nvidia-l4t-neutts-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-arm64-neutts"
+  mirrors:
+    - localai/localai-backends:master-nvidia-l4t-arm64-neutts
+- !!merge <<: *mlx
+  name: "mlx-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-mlx"
+  mirrors:
+    - localai/localai-backends:master-metal-darwin-arm64-mlx
+- !!merge <<: *mlx-vlm
+  name: "mlx-vlm-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-mlx-vlm"
+  mirrors:
+    - localai/localai-backends:master-metal-darwin-arm64-mlx-vlm
+- !!merge <<: *mlx-audio
+  name: "mlx-audio-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-mlx-audio"
+  mirrors:
+    - localai/localai-backends:master-metal-darwin-arm64-mlx-audio
+- !!merge <<: *kitten-tts
+  name: "kitten-tts-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-kitten-tts"
+  mirrors:
+    - localai/localai-backends:master-kitten-tts
 - !!merge <<: *huggingface
   name: "huggingface-development"
   uri: "quay.io/go-skynet/local-ai-backends:master-huggingface"
@@ -493,6 +646,16 @@
   uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-whisper"
   mirrors:
     - localai/localai-backends:latest-cpu-whisper
+- !!merge <<: *whispercpp
+  name: "metal-whisper"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-whisper"
+  mirrors:
+    - localai/localai-backends:latest-metal-darwin-arm64-whisper
+- !!merge <<: *whispercpp
+  name: "metal-whisper-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-whisper"
+  mirrors:
+    - localai/localai-backends:master-metal-darwin-arm64-whisper
 - !!merge <<: *whispercpp
   name: "cpu-whisper-development"
   uri: "quay.io/go-skynet/local-ai-backends:master-cpu-whisper"
@@ -579,6 +742,16 @@
   uri: "quay.io/go-skynet/local-ai-backends:master-cpu-stablediffusion-ggml"
   mirrors:
     - localai/localai-backends:master-cpu-stablediffusion-ggml
+- !!merge <<: *stablediffusionggml
+  name: "metal-stablediffusion-ggml"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-stablediffusion-ggml"
+  mirrors:
+    - localai/localai-backends:latest-metal-darwin-arm64-stablediffusion-ggml
+- !!merge <<: *stablediffusionggml
+  name: "metal-stablediffusion-ggml-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-stablediffusion-ggml"
+  mirrors:
+    - localai/localai-backends:master-metal-darwin-arm64-stablediffusion-ggml
 - !!merge <<: *stablediffusionggml
   name: "vulkan-stablediffusion-ggml"
   uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-vulkan-stablediffusion-ggml"
@@ -834,6 +1007,29 @@
     nvidia: "cuda12-diffusers-development"
     intel: "intel-diffusers-development"
     amd: "rocm-diffusers-development"
+    nvidia-l4t: "nvidia-l4t-diffusers-development"
+    metal: "metal-diffusers-development"
+    default: "cpu-diffusers-development"
+- !!merge <<: *diffusers
+  name: "cpu-diffusers"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-diffusers"
+  mirrors:
+    - localai/localai-backends:latest-cpu-diffusers
+- !!merge <<: *diffusers
+  name: "cpu-diffusers-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-cpu-diffusers"
+  mirrors:
+    - localai/localai-backends:master-cpu-diffusers
+- !!merge <<: *diffusers
+  name: "nvidia-l4t-diffusers"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-l4t-diffusers"
+  mirrors:
+    - localai/localai-backends:latest-gpu-nvidia-l4t-diffusers
+- !!merge <<: *diffusers
+  name: "nvidia-l4t-diffusers-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-l4t-diffusers"
+  mirrors:
+    - localai/localai-backends:master-gpu-nvidia-l4t-diffusers
 - !!merge <<: *diffusers
   name: "cuda12-diffusers"
   uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-diffusers"
@@ -874,6 +1070,16 @@
   uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-diffusers"
   mirrors:
     - localai/localai-backends:master-gpu-intel-diffusers
+- !!merge <<: *diffusers
+  name: "metal-diffusers"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-diffusers"
+  mirrors:
+    - localai/localai-backends:latest-metal-darwin-arm64-diffusers
+- !!merge <<: *diffusers
+  name: "metal-diffusers-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-diffusers"
+  mirrors:
+    - localai/localai-backends:master-metal-darwin-arm64-diffusers
   ## exllama2
 - !!merge <<: *exllama2
   name: "exllama2-development"
@@ -907,6 +1113,7 @@
     nvidia: "cuda12-kokoro-development"
     intel: "intel-kokoro-development"
     amd: "rocm-kokoro-development"
+    nvidia-l4t: "nvidia-l4t-kokoro-development"
 - !!merge <<: *kokoro
   name: "cuda11-kokoro-development"
   uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-11-kokoro"
@@ -932,6 +1139,16 @@
   uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-kokoro"
   mirrors:
     - localai/localai-backends:master-gpu-intel-kokoro
+- !!merge <<: *kokoro
+  name: "nvidia-l4t-kokoro"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-l4t-kokoro"
+  mirrors:
+    - localai/localai-backends:latest-gpu-nvidia-l4t-kokoro
+- !!merge <<: *kokoro
+  name: "nvidia-l4t-kokoro-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-l4t-kokoro"
+  mirrors:
+    - localai/localai-backends:master-gpu-nvidia-l4t-kokoro
 - !!merge <<: *kokoro
   name: "cuda11-kokoro"
   uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-11-kokoro"
@@ -1083,6 +1300,39 @@
   name: "chatterbox-development"
   capabilities:
     nvidia: "cuda12-chatterbox-development"
+    metal: "metal-chatterbox-development"
+    default: "cpu-chatterbox-development"
+    nvidia-l4t: "nvidia-l4t-arm64-chatterbox"
+- !!merge <<: *chatterbox
+  name: "cpu-chatterbox"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-chatterbox"
+  mirrors:
+    - localai/localai-backends:latest-cpu-chatterbox
+- !!merge <<: *chatterbox
+  name: "cpu-chatterbox-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-cpu-chatterbox"
+  mirrors:
+    - localai/localai-backends:master-cpu-chatterbox
+- !!merge <<: *chatterbox
+  name: "nvidia-l4t-arm64-chatterbox"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-l4t-arm64-chatterbox"
+  mirrors:
+    - localai/localai-backends:latest-gpu-nvidia-l4t-arm64-chatterbox
+- !!merge <<: *chatterbox
+  name: "nvidia-l4t-arm64-chatterbox-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-l4t-arm64-chatterbox"
+  mirrors:
+    - localai/localai-backends:master-gpu-nvidia-l4t-arm64-chatterbox
+- !!merge <<: *chatterbox
+  name: "metal-chatterbox"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-chatterbox"
+  mirrors:
+    - localai/localai-backends:latest-metal-darwin-arm64-chatterbox
+- !!merge <<: *chatterbox
+  name: "metal-chatterbox-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-metal-darwin-arm64-chatterbox"
+  mirrors:
+    - localai/localai-backends:master-metal-darwin-arm64-chatterbox
 - !!merge <<: *chatterbox
   name: "cuda12-chatterbox-development"
   uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-chatterbox"

backend/python/README.md

@@ -1,38 +1,190 @@
-# Common commands about conda environment
+# Python Backends for LocalAI
 
-## Create a new empty conda environment
+This directory contains Python-based AI backends for LocalAI, providing support for various AI models and hardware acceleration targets.
 
-```
-conda create --name <env-name> python=<your version> -y
+## Overview
 
-conda create --name autogptq python=3.11 -y
+The Python backends use a unified build system based on `libbackend.sh` that provides:
+- **Automatic virtual environment management** with support for both `uv` and `pip`
+- **Hardware-specific dependency installation** (CPU, CUDA, Intel, MLX, etc.)
+- **Portable Python support** for standalone deployments
+- **Consistent backend execution** across different environments
+
+## Available Backends
+
+### Core AI Models
+- **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
+- **mlx-audio** - Apple Silicon audio processing
+- **chatterbox** - TTS model
+- **kokoro** - TTS models
+
+### Computer Vision
+- **diffusers** - Stable Diffusion and image generation
+- **mlx-vlm** - Vision-language models for Apple Silicon
+- **rfdetr** - Object detection models
+
+### Specialized
+
+- **rerankers** - Text reranking models
+
+## Quick Start
+
+### Prerequisites
+- Python 3.10+ (default: 3.10.18)
+- `uv` package manager (recommended) or `pip`
+- Appropriate hardware drivers for your target (CUDA, Intel, etc.)
+
+### Installation
+
+Each backend can be installed individually:
+
+```bash
+# Navigate to a specific backend
+cd backend/python/transformers
+
+# Install dependencies
+make transformers
+# or
+bash install.sh
+
+# Run the backend
+make run
+# or
+bash run.sh
 ```
 
-## To activate the environment
+### Using the Unified Build System
 
-As of conda 4.4
-```
-conda activate autogptq
+The `libbackend.sh` script provides consistent commands across all backends:
+
+```bash
+# Source the library in your backend script
+source $(dirname $0)/../common/libbackend.sh
+
+# Install requirements (automatically handles hardware detection)
+installRequirements
+
+# Start the backend server
+startBackend $@
+
+# Run tests
+runUnittests
 ```
 
-The conda version older than 4.4
+## Hardware Targets
 
-```
-source activate autogptq
+The build system automatically detects and configures for different hardware:
+
+- **CPU** - Standard CPU-only builds
+- **CUDA** - NVIDIA GPU acceleration (supports CUDA 11/12)
+- **Intel** - Intel XPU/GPU optimization
+- **MLX** - Apple Silicon (M1/M2/M3) optimization
+- **HIP** - AMD GPU acceleration
+
+### Target-Specific Requirements
+
+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-intel.txt` - Intel-optimized packages
+- `requirements-mps.txt` - Apple Silicon packages
+
+## Configuration Options
+
+### Environment Variables
+
+- `PYTHON_VERSION` - Python version (default: 3.10)
+- `PYTHON_PATCH` - Python patch version (default: 18)
+- `BUILD_TYPE` - Force specific build target
+- `USE_PIP` - Use pip instead of uv (default: false)
+- `PORTABLE_PYTHON` - Enable portable Python builds
+- `LIMIT_TARGETS` - Restrict backend to specific targets
+
+### Example: CUDA 12 Only Backend
+
+```bash
+# In your backend script
+LIMIT_TARGETS="cublas12"
+source $(dirname $0)/../common/libbackend.sh
 ```
 
-## Install the packages to your environment
+### Example: Intel-Optimized Backend
 
-Sometimes you need to install the packages from the conda-forge channel
-
-By using `conda`
-```
-conda install <your-package-name>
-
-conda install -c conda-forge <your package-name>
+```bash
+# In your backend script
+LIMIT_TARGETS="intel"
+source $(dirname $0)/../common/libbackend.sh
 ```
 
-Or by using `pip`
+## Development
+
+### Adding a New Backend
+
+1. Create a new directory in `backend/python/`
+2. Copy the template structure from `common/template/`
+3. Implement your `backend.py` with the required gRPC interface
+4. Add appropriate requirements files for your target hardware
+5. Use `libbackend.sh` for consistent build and execution
+
+### Testing
+
+```bash
+# Run backend tests
+make test
+# or
+bash test.sh
 ```
-pip install <your-package-name>
+
+### Building
+
+```bash
+# Install dependencies
+make <backend-name>
+
+# Clean build artifacts
+make clean
 ```
+
+## Architecture
+
+Each backend follows a consistent structure:
+```
+backend-name/
+├── backend.py          # Main backend implementation
+├── requirements.txt    # Base dependencies
+├── requirements-*.txt  # Hardware-specific dependencies
+├── install.sh         # Installation script
+├── run.sh            # Execution script
+├── test.sh           # Test script
+├── Makefile          # Build targets
+└── test.py           # Unit tests
+```
+
+## Troubleshooting
+
+### Common Issues
+
+1. **Missing dependencies**: Ensure all requirements files are properly configured
+2. **Hardware detection**: Check that `BUILD_TYPE` matches your system
+3. **Python version**: Verify Python 3.10+ is available
+4. **Virtual environment**: Use `ensureVenv` to create/activate environments
+
+## Contributing
+
+When adding new backends or modifying existing ones:
+1. Follow the established directory structure
+2. Use `libbackend.sh` for consistent behavior
+3. Include appropriate requirements files for all target hardware
+4. Add comprehensive tests
+5. Update this README if adding new backend types

backend/python/bark/Makefile

@@ -1,29 +1,23 @@
 .PHONY: ttsbark
-ttsbark: protogen
+ttsbark:
 	bash install.sh
 
 .PHONY: run
-run: protogen
+run: ttsbark
 	@echo "Running bark..."
 	bash run.sh
 	@echo "bark run."
 
 .PHONY: test
-test: protogen
+test: ttsbark
 	@echo "Testing bark..."
 	bash test.sh
 	@echo "bark tested."
 
-.PHONY: protogen
-protogen: backend_pb2_grpc.py backend_pb2.py
-
 .PHONY: protogen-clean
 protogen-clean:
 	$(RM) backend_pb2_grpc.py backend_pb2.py
 
-backend_pb2_grpc.py backend_pb2.py:
-	python3 -m grpc_tools.protoc -I../.. -I./ --python_out=. --grpc_python_out=. backend.proto
-
 .PHONY: clean
 clean: protogen-clean
 	rm -rf venv __pycache__

backend/python/bark/requirements-intel.txt

@@ -1,5 +1,5 @@
 --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
-intel-extension-for-pytorch==2.3.110+xpu
+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

backend/python/bark/requirements.txt

@@ -1,4 +1,4 @@
 bark==0.1.5
-grpcio==1.71.0
+grpcio==1.76.0
 protobuf
 certifi

backend/python/chatterbox/Makefile

@@ -1,29 +1,23 @@
-.PHONY: coqui
-coqui: protogen
+.PHONY: chatterbox
+chatterbox:
 	bash install.sh
 
 .PHONY: run
-run: protogen
+run: chatterbox
 	@echo "Running coqui..."
 	bash run.sh
 	@echo "coqui run."
 
 .PHONY: test
-test: protogen
+test: chatterbox
 	@echo "Testing coqui..."
 	bash test.sh
 	@echo "coqui tested."
 
-.PHONY: protogen
-protogen: backend_pb2_grpc.py backend_pb2.py
-
 .PHONY: protogen-clean
 protogen-clean:
 	$(RM) backend_pb2_grpc.py backend_pb2.py
 
-backend_pb2_grpc.py backend_pb2.py:
-	python3 -m grpc_tools.protoc -I../.. -I./ --python_out=. --grpc_python_out=. backend.proto
-
 .PHONY: clean
 clean: protogen-clean
 	rm -rf venv __pycache__

backend/python/chatterbox/backend.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 """
-This is an extra gRPC server of LocalAI for Bark TTS
+This is an extra gRPC server of LocalAI for Chatterbox TTS
 """
 from concurrent import futures
 import time
@@ -14,15 +14,98 @@ 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):
@@ -41,10 +124,34 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
         else:
             print("CUDA is not available", file=sys.stderr)
             device = "cpu"
-
+        mps_available = hasattr(torch.backends, "mps") and torch.backends.mps.is_available()
+        if mps_available:
+            device = "mps"
         if not torch.cuda.is_available() and request.CUDA:
             return backend_pb2.Result(success=False, message="CUDA is not available")
 
+
+        options = request.Options
+
+        # empty dict
+        self.options = {}
+
+        # 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):
@@ -54,10 +161,14 @@ 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)
-            self.model = ChatterboxTTS.from_pretrained(device=device)
+            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)
         except Exception as err:
             return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
         # Implement your logic here for the LoadModel service
@@ -66,14 +177,43 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
 
     def TTS(self, request, context):
         try:
-            # Generate audio using ChatterboxTTS
+            kwargs = {}
+
+            if "language" in self.options:
+                kwargs["language_id"] = self.options["language"]
             if self.AudioPath is not None:
-                wav = self.model.generate(request.text, audio_prompt_path=self.AudioPath)
+                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)
             else:
-                wav = self.model.generate(request.text)
-            
-            # Save the generated audio
-            ta.save(request.dst, wav, self.model.sr)
+                # 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)
             
         except Exception as err:
             return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")

backend/python/chatterbox/install.sh

@@ -15,5 +15,6 @@ 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"
 
 installRequirements

backend/python/chatterbox/requirements-cpu.txt

@@ -1,5 +1,9 @@
+--extra-index-url https://download.pytorch.org/whl/cpu
 accelerate
-torch==2.6.0
-torchaudio==2.6.0
-transformers==4.46.3
-chatterbox-tts
+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

backend/python/chatterbox/requirements-cublas11.txt

@@ -2,5 +2,7 @@
 torch==2.6.0+cu118
 torchaudio==2.6.0+cu118
 transformers==4.46.3
-chatterbox-tts
+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-cublas12.txt

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

@@ -1,6 +1,8 @@
 --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
+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-intel.txt

@@ -2,10 +2,11 @@
 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
+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
 oneccl_bind_pt==2.3.100+xpu
 optimum[openvino]
-setuptools
-accelerate
+setuptools

backend/python/chatterbox/requirements-l4t.txt

@@ -0,0 +1,7 @@
+--extra-index-url https://pypi.jetson-ai-lab.io/jp6/cu126/
+torch
+torchaudio
+transformers
+numpy>=1.24.0,<1.26.0
+chatterbox-tts@git+https://git@github.com/mudler/chatterbox.git@faster
+accelerate

backend/python/chatterbox/requirements.txt

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

backend/python/common/libbackend.sh

@@ -1,6 +1,6 @@
+#!/usr/bin/env bash
+set -euo pipefail
 
-
-# init handles the setup of the library
 # 
 # use the library by adding the following line to a script:
 # source $(dirname $0)/../common/libbackend.sh
@@ -17,29 +17,182 @@
 # LIMIT_TARGETS="cublas12"
 # source $(dirname $0)/../common/libbackend.sh
 #
+# You can switch between uv (conda-like) and pip installation methods by setting USE_PIP:
+# USE_PIP=true source $(dirname $0)/../common/libbackend.sh
+#
+# ===================== user-configurable defaults =====================
+PYTHON_VERSION="${PYTHON_VERSION:-3.10}"      # e.g. 3.10 / 3.11 / 3.12 / 3.13
+PYTHON_PATCH="${PYTHON_PATCH:-18}"            # e.g. 18 -> 3.10.18 ; 13 -> 3.11.13
+PY_STANDALONE_TAG="${PY_STANDALONE_TAG:-20250818}"  # release tag date
+# Enable/disable bundling of a portable Python build
+PORTABLE_PYTHON="${PORTABLE_PYTHON:-false}"
 
-PYTHON_VERSION="3.10"
+# If you want to fully pin the filename (including tuned CPU targets), set:
+# PORTABLE_PY_FILENAME="cpython-3.10.18+20250818-x86_64_v3-unknown-linux-gnu-install_only.tar.gz"
+: "${PORTABLE_PY_FILENAME:=}"
+: "${PORTABLE_PY_SHA256:=}"  # optional; if set we verify the download
+# =====================================================================
 
+# Default to uv if USE_PIP is not set
+if [ "x${USE_PIP:-}" == "x" ]; then
+    USE_PIP=false
+fi
+
+# ----------------------- helpers -----------------------
+function _is_musl() {
+    # detect musl (Alpine, etc)
+    if command -v ldd >/dev/null 2>&1; then
+        ldd --version 2>&1 | grep -qi musl && return 0
+    fi
+    # busybox-ish fallback
+    if command -v getconf >/dev/null 2>&1; then
+        getconf GNU_LIBC_VERSION >/dev/null 2>&1 || return 0
+    fi
+    return 1
+}
+
+function _triple() {
+    local os="" arch="" libc="gnu"
+    case "$(uname -s)" in
+        Linux*)  os="unknown-linux" ;;
+        Darwin*) os="apple-darwin" ;;
+        MINGW*|MSYS*|CYGWIN*) os="pc-windows-msvc" ;;  # best-effort for Git Bash
+        *) echo "Unsupported OS $(uname -s)"; exit 1;;
+    esac
+
+    case "$(uname -m)" in
+        x86_64) arch="x86_64" ;;
+        aarch64|arm64) arch="aarch64" ;;
+        armv7l) arch="armv7" ;;
+        i686|i386) arch="i686" ;;
+        ppc64le) arch="ppc64le" ;;
+        s390x) arch="s390x" ;;
+        riscv64) arch="riscv64" ;;
+        *) echo "Unsupported arch $(uname -m)"; exit 1;;
+    esac
+
+    if [[ "$os" == "unknown-linux" ]]; then
+        if _is_musl; then
+            libc="musl"
+        else
+            libc="gnu"
+        fi
+        echo "${arch}-${os}-${libc}"
+    else
+        echo "${arch}-${os}"
+    fi
+}
+
+function _portable_dir() {
+    echo "${EDIR}/python"
+}
+
+function _portable_bin() {
+    # python-build-standalone puts python in ./bin
+    echo "$(_portable_dir)/bin"
+}
+
+function _portable_python() {
+    if [ -x "$(_portable_bin)/python3" ]; then
+        echo "$(_portable_bin)/python3"
+    else
+        echo "$(_portable_bin)/python"
+    fi
+}
+
+
+# macOS loader env for the portable CPython
+_macosPortableEnv() {
+  if [ "$(uname -s)" = "Darwin" ]; then
+    export DYLD_LIBRARY_PATH="$(_portable_dir)/lib${DYLD_LIBRARY_PATH:+:${DYLD_LIBRARY_PATH}}"
+    export DYLD_FALLBACK_LIBRARY_PATH="$(_portable_dir)/lib${DYLD_FALLBACK_LIBRARY_PATH:+:${DYLD_FALLBACK_LIBRARY_PATH}}"
+  fi
+}
+
+# Good hygiene on macOS for downloaded/extracted trees
+_unquarantinePortablePython() {
+  if [ "$(uname -s)" = "Darwin" ]; then
+    command -v xattr >/dev/null 2>&1 && xattr -dr com.apple.quarantine "$(_portable_dir)" || true
+  fi
+}
+
+# ------------------ ### PORTABLE PYTHON ------------------
+function ensurePortablePython() {
+    local pdir="$(_portable_dir)"
+    local pbin="$(_portable_bin)"
+    local pyexe
+
+    if [ -x "${pbin}/python3" ] || [ -x "${pbin}/python" ]; then
+        _macosPortableEnv
+        return 0
+    fi
+
+    mkdir -p "${pdir}"
+    local triple="$(_triple)"
+
+    local full_ver="${PYTHON_VERSION}.${PYTHON_PATCH}"
+    local fn=""
+    if [ -n "${PORTABLE_PY_FILENAME}" ]; then
+        fn="${PORTABLE_PY_FILENAME}"
+    else
+        # generic asset name: cpython-<full_ver>+<tag>-<triple>-install_only.tar.gz
+        fn="cpython-${full_ver}+${PY_STANDALONE_TAG}-${triple}-install_only.tar.gz"
+    fi
+
+    local url="https://github.com/astral-sh/python-build-standalone/releases/download/${PY_STANDALONE_TAG}/${fn}"
+    local tmp="${pdir}/${fn}"
+    echo "Downloading portable Python: ${fn}"
+    # curl with retries; fall back to wget if needed
+    if command -v curl >/dev/null 2>&1; then
+        curl -L --fail --retry 3 --retry-delay 1 -o "${tmp}" "${url}"
+    else
+        wget -O "${tmp}" "${url}"
+    fi
+
+    if [ -n "${PORTABLE_PY_SHA256}" ]; then
+        echo "${PORTABLE_PY_SHA256}  ${tmp}" | sha256sum -c -
+    fi
+
+    echo "Extracting ${fn} -> ${pdir}"
+    # always a .tar.gz (we purposely choose install_only)
+    tar -xzf "${tmp}" -C "${pdir}"
+    rm -f "${tmp}"
+
+    # Some archives nest a directory; if so, flatten to ${pdir}
+    # Find the first dir with a 'bin/python*'
+    local inner
+    inner="$(find "${pdir}" -type f -path "*/bin/python*" -maxdepth 3 2>/dev/null | head -n1 || true)"
+    if [ -n "${inner}" ]; then
+        local inner_root
+        inner_root="$(dirname "$(dirname "${inner}")")" # .../bin -> root
+        if [ "${inner_root}" != "${pdir}" ]; then
+            # move contents up one level
+            shopt -s dotglob
+            mv "${inner_root}/"* "${pdir}/"
+            rm -rf "${inner_root}"
+            shopt -u dotglob
+        fi
+    fi
+
+    _unquarantinePortablePython
+    _macosPortableEnv
+    # Make sure it's runnable
+    pyexe="$(_portable_python)"
+    "${pyexe}" -V
+}
+
+# init handles the setup of the library
 function init() {
-    # Name of the backend (directory name)
     BACKEND_NAME=${PWD##*/}
-
-    # Path where all backends files are
-    MY_DIR=$(realpath `dirname $0`)
-
-    # Build type
+    MY_DIR=$(realpath "$(dirname "$0")")
     BUILD_PROFILE=$(getBuildProfile)
 
-    # Environment directory
     EDIR=${MY_DIR}
-
-    # Allow to specify a custom env dir for shared environments
-    if [ "x${ENV_DIR}" != "x" ]; then
+    if [ "x${ENV_DIR:-}" != "x" ]; then
         EDIR=${ENV_DIR}
     fi
 
-    # If a backend has defined a list of valid build profiles...
-    if [ ! -z "${LIMIT_TARGETS}" ]; then
+    if [ ! -z "${LIMIT_TARGETS:-}" ]; then
         isValidTarget=$(checkTargets ${LIMIT_TARGETS})
         if [ ${isValidTarget} != true ]; then
             echo "${BACKEND_NAME} can only be used on the following targets: ${LIMIT_TARGETS}"
@@ -50,6 +203,7 @@ function init() {
     echo "Initializing libbackend for ${BACKEND_NAME}"
 }
 
+
 # getBuildProfile will inspect the system to determine which build profile is appropriate:
 # returns one of the following:
 # - cublas11
@@ -57,53 +211,140 @@ function init() {
 # - hipblas
 # - intel
 function getBuildProfile() {
-    # First check if we are a cublas build, and if so report the correct build profile
-    if [ x"${BUILD_TYPE}" == "xcublas" ]; then
-        if [ ! -z ${CUDA_MAJOR_VERSION} ]; then
-            # If we have been given a CUDA version, we trust it
+    if [ x"${BUILD_TYPE:-}" == "xcublas" ]; then
+        if [ ! -z "${CUDA_MAJOR_VERSION:-}" ]; then
             echo ${BUILD_TYPE}${CUDA_MAJOR_VERSION}
         else
-            # We don't know what version of cuda we are, so we report ourselves as a generic cublas
             echo ${BUILD_TYPE}
         fi
         return 0
     fi
 
-    # If /opt/intel exists, then we are doing an intel/ARC build
     if [ -d "/opt/intel" ]; then
         echo "intel"
         return 0
     fi
 
-    # If for any other values of BUILD_TYPE, we don't need any special handling/discovery
-    if [ ! -z ${BUILD_TYPE} ]; then
+    if [ -n "${BUILD_TYPE:-}" ]; then
         echo ${BUILD_TYPE}
         return 0
     fi
 
-    # If there is no BUILD_TYPE set at all, set a build-profile value of CPU, we aren't building for any GPU targets
     echo "cpu"
 }
 
+
+# Make the venv relocatable:
+# - rewrite venv/bin/python{,3} to relative symlinks into $(_portable_dir)
+# - normalize entrypoint shebangs to /usr/bin/env python3
+_makeVenvPortable() {
+    local venv_dir="${EDIR}/venv"
+    local vbin="${venv_dir}/bin"
+
+    [ -d "${vbin}" ] || return 0
+
+    # 1) Replace python symlinks with relative ones to ../../python/bin/python3
+    #    (venv/bin -> venv -> EDIR -> python/bin)
+    local rel_py='../../python/bin/python3'
+
+    for name in python3 python; do
+        if [ -e "${vbin}/${name}" ] || [ -L "${vbin}/${name}" ]; then
+            rm -f "${vbin}/${name}"
+        fi
+    done
+    ln -s "${rel_py}" "${vbin}/python3"
+    ln -s "python3" "${vbin}/python"
+
+    # 2) Rewrite shebangs of entry points to use env, so the venv is relocatable
+    #    Only touch text files that start with #! and reference the current venv.
+    local ve_abs="${vbin}/python"
+    local sed_i=(sed -i)
+    # macOS/BSD sed needs a backup suffix; GNU sed doesn't. Make it portable:
+    if sed --version >/dev/null 2>&1; then
+        sed_i=(sed -i)
+    else
+        sed_i=(sed -i '')
+    fi
+
+    for f in "${vbin}"/*; do
+        [ -f "$f" ] || continue
+        # Fast path: check first two bytes (#!)
+        head -c2 "$f" 2>/dev/null | grep -q '^#!' || continue
+        # Only rewrite if the shebang mentions the (absolute) venv python
+        if head -n1 "$f" | grep -Fq "${ve_abs}"; then
+            "${sed_i[@]}" '1s|^#!.*$|#!/usr/bin/env python3|' "$f"
+            chmod +x "$f" 2>/dev/null || true
+        fi
+    done
+}
+
+
 # ensureVenv makes sure that the venv for the backend both exists, and is activated.
 #
 # This function is idempotent, so you can call it as many times as you want and it will
 # always result in an activated virtual environment
 function ensureVenv() {
+    local interpreter=""
+
+    if [ "x${PORTABLE_PYTHON}" == "xtrue" ] || [ -e "$(_portable_python)" ]; then
+        echo "Using portable Python"
+        ensurePortablePython
+        interpreter="$(_portable_python)"
+    else
+        # Prefer system python${PYTHON_VERSION}, else python3, else fall back to bundled
+        if command -v python${PYTHON_VERSION} >/dev/null 2>&1; then
+            interpreter="python${PYTHON_VERSION}"
+        elif command -v python3 >/dev/null 2>&1; then
+            interpreter="python3"
+        else
+            echo "No suitable system Python found, bootstrapping portable build..."
+            ensurePortablePython
+            interpreter="$(_portable_python)"
+        fi
+    fi
+
     if [ ! -d "${EDIR}/venv" ]; then
-        uv venv --python ${PYTHON_VERSION} ${EDIR}/venv
-        echo "virtualenv created"
+        if [ "x${USE_PIP}" == "xtrue" ]; then
+            "${interpreter}" -m venv --copies "${EDIR}/venv"
+            source "${EDIR}/venv/bin/activate"
+            "${interpreter}" -m pip install --upgrade pip
+        else
+            if [ "x${PORTABLE_PYTHON}" == "xtrue" ]; then
+                uv venv --python "${interpreter}" "${EDIR}/venv"
+            else
+                uv venv --python "${PYTHON_VERSION}" "${EDIR}/venv"
+            fi
+        fi
+        if [ "x${PORTABLE_PYTHON}" == "xtrue" ]; then
+            _makeVenvPortable
+        fi
     fi
 
-    # Source if we are not already in a Virtual env
-    if [ "x${VIRTUAL_ENV}" != "x${EDIR}/venv" ]; then
-        source ${EDIR}/venv/bin/activate
-        echo "virtualenv activated"
+    # We call it here to make sure that when we source a venv we can still use python as expected
+    if [ -x "$(_portable_python)" ]; then
+        _macosPortableEnv
     fi
 
-    echo "activated virtualenv has been ensured"
+    if [ "x${VIRTUAL_ENV:-}" != "x${EDIR}/venv" ]; then
+        source "${EDIR}/venv/bin/activate"
+    fi
 }
 
+
+function runProtogen() {
+    ensureVenv
+    if [ "x${USE_PIP}" == "xtrue" ]; then
+        pip install grpcio-tools
+    else
+        uv pip install grpcio-tools
+    fi
+    pushd "${EDIR}" >/dev/null
+        # use the venv python (ensures correct interpreter & sys.path)
+        python -m grpc_tools.protoc -I../../ -I./ --python_out=. --grpc_python_out=. backend.proto
+    popd >/dev/null
+}
+
+
 # installRequirements looks for several requirements files and if they exist runs the install for them in order
 #
 #  - requirements-install.txt
@@ -111,7 +352,7 @@ function ensureVenv() {
 #  - requirements-${BUILD_TYPE}.txt
 #  - requirements-${BUILD_PROFILE}.txt
 #
-# BUILD_PROFILE is a pore specific version of BUILD_TYPE, ex: cuda-11 or cuda-12
+# BUILD_PROFILE is a more specific version of BUILD_TYPE, ex: cuda-11 or cuda-12
 # it can also include some options that we do not have BUILD_TYPES for, ex: intel
 #
 # NOTE: for BUILD_PROFILE==intel, this function does NOT automatically use the Intel python package index.
@@ -127,36 +368,41 @@ function ensureVenv() {
 # installRequirements
 function installRequirements() {
     ensureVenv
-
-    # These are the requirements files we will attempt to install, in order
     declare -a requirementFiles=(
         "${EDIR}/requirements-install.txt"
         "${EDIR}/requirements.txt"
-        "${EDIR}/requirements-${BUILD_TYPE}.txt"
+        "${EDIR}/requirements-${BUILD_TYPE:-}.txt"
     )
 
-    if [ "x${BUILD_TYPE}" != "x${BUILD_PROFILE}" ]; then
+    if [ "x${BUILD_TYPE:-}" != "x${BUILD_PROFILE}" ]; then
         requirementFiles+=("${EDIR}/requirements-${BUILD_PROFILE}.txt")
     fi
-
-    # if BUILD_TYPE is empty, we are a CPU build, so we should try to install the CPU requirements
-    if [ "x${BUILD_TYPE}" == "x" ]; then
+    if [ "x${BUILD_TYPE:-}" == "x" ]; then
         requirementFiles+=("${EDIR}/requirements-cpu.txt")
     fi
-
     requirementFiles+=("${EDIR}/requirements-after.txt")
-
-    if [ "x${BUILD_TYPE}" != "x${BUILD_PROFILE}" ]; then
+    if [ "x${BUILD_TYPE:-}" != "x${BUILD_PROFILE}" ]; then
         requirementFiles+=("${EDIR}/requirements-${BUILD_PROFILE}-after.txt")
     fi
 
+    # This is needed to build wheels that e.g. depends on Python.h
+    if [ "x${PORTABLE_PYTHON}" == "xtrue" ]; then
+        export C_INCLUDE_PATH="${C_INCLUDE_PATH:-}:$(_portable_dir)/include/python${PYTHON_VERSION}"
+    fi
+
     for reqFile in ${requirementFiles[@]}; do
-        if [ -f ${reqFile} ]; then
+        if [ -f "${reqFile}" ]; then
             echo "starting requirements install for ${reqFile}"
-            uv pip install ${EXTRA_PIP_INSTALL_FLAGS} --requirement ${reqFile}
+            if [ "x${USE_PIP}" == "xtrue" ]; then
+                pip install ${EXTRA_PIP_INSTALL_FLAGS:-} --requirement "${reqFile}"
+            else
+                uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} --requirement "${reqFile}"
+            fi
             echo "finished requirements install for ${reqFile}"
         fi
     done
+
+    runProtogen
 }
 
 # startBackend discovers and runs the backend GRPC server
@@ -174,18 +420,18 @@ function installRequirements() {
 #  - ${BACKEND_NAME}.py
 function startBackend() {
     ensureVenv
-
-    if [ ! -z ${BACKEND_FILE} ]; then
-        exec ${EDIR}/venv/bin/python ${BACKEND_FILE} $@
+    if [ ! -z "${BACKEND_FILE:-}" ]; then
+        exec "${EDIR}/venv/bin/python" "${BACKEND_FILE}" "$@"
     elif [ -e "${MY_DIR}/server.py" ]; then
-        exec ${EDIR}/venv/bin/python ${MY_DIR}/server.py $@
+        exec "${EDIR}/venv/bin/python" "${MY_DIR}/server.py" "$@"
     elif [ -e "${MY_DIR}/backend.py" ]; then
-        exec ${EDIR}/venv/bin/python ${MY_DIR}/backend.py $@
+        exec "${EDIR}/venv/bin/python" "${MY_DIR}/backend.py" "$@"
     elif [ -e "${MY_DIR}/${BACKEND_NAME}.py" ]; then
-        exec ${EDIR}/venv/bin/python ${MY_DIR}/${BACKEND_NAME}.py $@
+        exec "${EDIR}/venv/bin/python" "${MY_DIR}/${BACKEND_NAME}.py" "$@"
     fi
 }
 
+
 # runUnittests discovers and runs python unittests
 #
 # You can specify a specific test file to use by setting TEST_FILE before calling runUnittests.
@@ -198,41 +444,36 @@ function startBackend() {
 # be default a file named test.py in the backends directory will be used
 function runUnittests() {
     ensureVenv
-
-    if [ ! -z ${TEST_FILE} ]; then
-        testDir=$(dirname `realpath ${TEST_FILE}`)
-        testFile=$(basename ${TEST_FILE})
-        pushd ${testDir}
-        python -m unittest ${testFile}
-        popd
+    if [ ! -z "${TEST_FILE:-}" ]; then
+        testDir=$(dirname "$(realpath "${TEST_FILE}")")
+        testFile=$(basename "${TEST_FILE}")
+        pushd "${testDir}" >/dev/null
+        python -m unittest "${testFile}"
+        popd >/dev/null
     elif [ -f "${MY_DIR}/test.py" ]; then
-        pushd ${MY_DIR}
+        pushd "${MY_DIR}" >/dev/null
         python -m unittest test.py
-        popd
+        popd >/dev/null
     else
         echo "no tests defined for ${BACKEND_NAME}"
     fi
 }
 
+
 ##################################################################################
 # Below here are helper functions not intended to be used outside of the library #
 ##################################################################################
 
 # checkTargets determines if the current BUILD_TYPE or BUILD_PROFILE is in a list of valid targets
 function checkTargets() {
-    # Collect all provided targets into a variable and...
     targets=$@
-    # ...convert it into an array
     declare -a targets=($targets)
-
     for target in ${targets[@]}; do
-        if [ "x${BUILD_TYPE}" == "x${target}" ]; then
-            echo true
-            return 0
+        if [ "x${BUILD_TYPE:-}" == "x${target}" ]; then
+            echo true; return 0
         fi
         if [ "x${BUILD_PROFILE}" == "x${target}" ]; then
-            echo true
-            return 0
+            echo true; return 0
         fi
     done
     echo false

backend/python/common/template/Makefile

@@ -3,18 +3,11 @@
 .PHONY: install
 install:
 	bash install.sh
-	$(MAKE) protogen
-
-.PHONY: protogen
-protogen: backend_pb2_grpc.py backend_pb2.py
 
 .PHONY: protogen-clean
 protogen-clean:
 	$(RM) backend_pb2_grpc.py backend_pb2.py
 
-backend_pb2_grpc.py backend_pb2.py:
-	bash protogen.sh
-
 .PHONY: clean
 clean: protogen-clean
 	rm -rf venv __pycache__

backend/python/common/template/protogen.sh

@@ -8,6 +8,4 @@ else
     source $backend_dir/../common/libbackend.sh
 fi
 
-ensureVenv
-
-python3 -m grpc_tools.protoc -I../.. -I./ --python_out=. --grpc_python_out=. backend.proto
+runProtogen

backend/python/common/template/requirements-intel.txt

@@ -1,5 +1,5 @@
 --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
-oneccl_bind_pt==2.3.100+xpu
+intel-extension-for-pytorch==2.8.10+xpu
+torch==2.8.0
+oneccl_bind_pt==2.8.0+xpu
 optimum[openvino]

backend/python/common/template/requirements.txt

@@ -1,3 +1,3 @@
-grpcio==1.71.0
+grpcio==1.76.0
 protobuf
 grpcio-tools

backend/python/coqui/Makefile

@@ -1,29 +1,23 @@
 .PHONY: coqui
-coqui: protogen
+coqui:
 	bash install.sh
 
 .PHONY: run
-run: protogen
+run: coqui
 	@echo "Running coqui..."
 	bash run.sh
 	@echo "coqui run."
 
 .PHONY: test
-test: protogen
+test: coqui
 	@echo "Testing coqui..."
 	bash test.sh
 	@echo "coqui tested."
 
-.PHONY: protogen
-protogen: backend_pb2_grpc.py backend_pb2.py
-
 .PHONY: protogen-clean
 protogen-clean:
 	$(RM) backend_pb2_grpc.py backend_pb2.py
 
-backend_pb2_grpc.py backend_pb2.py:
-	python3 -m grpc_tools.protoc -I../.. -I./ --python_out=. --grpc_python_out=. backend.proto
-
 .PHONY: clean
 clean: protogen-clean
 	rm -rf venv __pycache__

backend/python/coqui/backend.py

@@ -40,7 +40,9 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
         else:
             print("CUDA is not available", file=sys.stderr)
             device = "cpu"
-
+        mps_available = hasattr(torch.backends, "mps") and torch.backends.mps.is_available()
+        if mps_available:
+            device = "mps"
         if not torch.cuda.is_available() and request.CUDA:
             return backend_pb2.Result(success=False, message="CUDA is not available")
 

backend/python/coqui/requirements.txt

@@ -1,4 +1,4 @@
-grpcio==1.71.0
+grpcio==1.76.0
 protobuf
 certifi
 packaging==24.1

backend/python/diffusers/Makefile

@@ -12,28 +12,22 @@ export SKIP_CONDA=1
 endif
 
 .PHONY: diffusers
-diffusers: protogen
+diffusers:
 	bash install.sh
 
 .PHONY: run
-run: protogen
+run: diffusers
 	@echo "Running diffusers..."
 	bash run.sh
 	@echo "Diffusers run."
 
-test: protogen
+test: diffusers
 	bash test.sh
 
-.PHONY: protogen
-protogen: backend_pb2_grpc.py backend_pb2.py
-
 .PHONY: protogen-clean
 protogen-clean:
 	$(RM) backend_pb2_grpc.py backend_pb2.py
 
-backend_pb2_grpc.py backend_pb2.py:
-	python3 -m grpc_tools.protoc -I../.. -I./ --python_out=. --grpc_python_out=. backend.proto
-
 .PHONY: clean
 clean: protogen-clean
 	rm -rf venv __pycache__

backend/python/diffusers/backend.py

@@ -18,7 +18,7 @@ import backend_pb2_grpc
 import grpc
 
 from diffusers import SanaPipeline, StableDiffusion3Pipeline, StableDiffusionXLPipeline, StableDiffusionDepth2ImgPipeline, DPMSolverMultistepScheduler, StableDiffusionPipeline, DiffusionPipeline, \
-    EulerAncestralDiscreteScheduler, FluxPipeline, FluxTransformer2DModel
+    EulerAncestralDiscreteScheduler, FluxPipeline, FluxTransformer2DModel, QwenImageEditPipeline, AutoencoderKLWan, WanPipeline, WanImageToVideoPipeline
 from diffusers import StableDiffusionImg2ImgPipeline, AutoPipelineForText2Image, ControlNetModel, StableVideoDiffusionPipeline, Lumina2Text2ImgPipeline
 from diffusers.pipelines.stable_diffusion import safety_checker
 from diffusers.utils import load_image, export_to_video
@@ -65,6 +65,21 @@ from diffusers.schedulers import (
     UniPCMultistepScheduler,
 )
 
+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
+
 
 # The scheduler list mapping was taken from here: https://github.com/neggles/animatediff-cli/blob/6f336f5f4b5e38e85d7f06f1744ef42d0a45f2a7/src/animatediff/schedulers.py#L39
 # Credits to https://github.com/neggles
@@ -169,8 +184,26 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
                 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
 
+            # From options, extract if present "torch_dtype" and set it to the appropriate type
+            if "torch_dtype" in self.options:
+                if self.options["torch_dtype"] == "fp16":
+                    torchType = torch.float16
+                elif self.options["torch_dtype"] == "bf16":
+                    torchType = torch.bfloat16
+                elif self.options["torch_dtype"] == "fp32":
+                    torchType = torch.float32
+                # remove it from options
+                del self.options["torch_dtype"]
+
             print(f"Options: {self.options}", file=sys.stderr)
 
             local = False
@@ -234,6 +267,9 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
             elif request.PipelineType == "DiffusionPipeline":
                 self.pipe = DiffusionPipeline.from_pretrained(request.Model,
                                                               torch_dtype=torchType)
+            elif request.PipelineType == "QwenImageEditPipeline":
+                self.pipe = QwenImageEditPipeline.from_pretrained(request.Model,
+                                                                 torch_dtype=torchType)
             elif request.PipelineType == "VideoDiffusionPipeline":
                 self.txt2vid = True
                 self.pipe = DiffusionPipeline.from_pretrained(request.Model,
@@ -302,6 +338,32 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
                     torch_dtype=torch.bfloat16)
                 self.pipe.vae.to(torch.bfloat16)
                 self.pipe.text_encoder.to(torch.bfloat16)
+            elif request.PipelineType == "WanPipeline":
+                # WAN2.2 pipeline requires special VAE handling
+                vae = AutoencoderKLWan.from_pretrained(
+                    request.Model, 
+                    subfolder="vae", 
+                    torch_dtype=torch.float32
+                )
+                self.pipe = WanPipeline.from_pretrained(
+                    request.Model,
+                    vae=vae,
+                    torch_dtype=torchType
+                )
+                self.txt2vid = True  # WAN2.2 is a text-to-video pipeline
+            elif request.PipelineType == "WanImageToVideoPipeline":
+                # WAN2.2 image-to-video pipeline
+                vae = AutoencoderKLWan.from_pretrained(
+                    request.Model, 
+                    subfolder="vae", 
+                    torch_dtype=torch.float32
+                )
+                self.pipe = WanImageToVideoPipeline.from_pretrained(
+                    request.Model,
+                    vae=vae,
+                    torch_dtype=torchType
+                )
+                self.img2vid = True  # WAN2.2 image-to-video pipeline
 
             if CLIPSKIP and request.CLIPSkip != 0:
                 self.clip_skip = request.CLIPSkip
@@ -336,6 +398,9 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
             device = "cpu" if not request.CUDA else "cuda"
             if XPU:
                 device = "xpu"
+            mps_available = hasattr(torch.backends, "mps") and torch.backends.mps.is_available()
+            if mps_available:
+                device = "mps"
             self.device = device
             if request.LoraAdapter:
                 # Check if its a local file and not a directory ( we load lora differently for a safetensor file )
@@ -440,11 +505,24 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
             "num_inference_steps": steps,
         }
 
-        if request.src != "" and not self.controlnet and not self.img2vid:
-            image = Image.open(request.src)
+        # Handle image source: prioritize RefImages over request.src
+        image_src = None
+        if hasattr(request, 'ref_images') and request.ref_images and len(request.ref_images) > 0:
+            # Use the first reference image if available
+            image_src = request.ref_images[0]
+            print(f"Using reference image: {image_src}", file=sys.stderr)
+        elif request.src != "":
+            # Fall back to request.src if no ref_images
+            image_src = request.src
+            print(f"Using source image: {image_src}", file=sys.stderr)
+        else:
+            print("No image source provided", file=sys.stderr)
+        
+        if image_src and not self.controlnet and not self.img2vid:
+            image = Image.open(image_src)
             options["image"] = image
-        elif self.controlnet and request.src:
-            pose_image = load_image(request.src)
+        elif self.controlnet and image_src:
+            pose_image = load_image(image_src)
             options["image"] = pose_image
 
         if CLIPSKIP and self.clip_skip != 0:
@@ -486,7 +564,11 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
 
         if self.img2vid:
             # Load the conditioning image
-            image = load_image(request.src)
+            if image_src:
+                image = load_image(image_src)
+            else:
+                # Fallback to request.src for img2vid if no ref_images
+                image = load_image(request.src)
             image = image.resize((1024, 576))
 
             generator = torch.manual_seed(request.seed)
@@ -523,6 +605,96 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
 
         return backend_pb2.Result(message="Media generated", success=True)
 
+    def GenerateVideo(self, request, context):
+        try:
+            prompt = request.prompt
+            if not prompt:
+                return backend_pb2.Result(success=False, message="No prompt provided for video generation")
+
+            # Set default values from request or use defaults
+            num_frames = request.num_frames if request.num_frames > 0 else 81
+            fps = request.fps if request.fps > 0 else 16
+            cfg_scale = request.cfg_scale if request.cfg_scale > 0 else 4.0
+            num_inference_steps = request.step if request.step > 0 else 40
+            
+            # Prepare generation parameters
+            kwargs = {
+                "prompt": prompt,
+                "negative_prompt": request.negative_prompt if request.negative_prompt else "",
+                "height": request.height if request.height > 0 else 720,
+                "width": request.width if request.width > 0 else 1280,
+                "num_frames": num_frames,
+                "guidance_scale": cfg_scale,
+                "num_inference_steps": num_inference_steps,
+            }
+
+            # Add custom options from self.options (including guidance_scale_2 if specified)
+            kwargs.update(self.options)
+
+            # Set seed if provided
+            if request.seed > 0:
+                kwargs["generator"] = torch.Generator(device=self.device).manual_seed(request.seed)
+
+            # Handle start and end images for video generation
+            if request.start_image:
+                kwargs["start_image"] = load_image(request.start_image)
+            if request.end_image:
+                kwargs["end_image"] = load_image(request.end_image)
+
+            print(f"Generating video with {kwargs=}", file=sys.stderr)
+
+            # Generate video frames based on pipeline type
+            if self.PipelineType == "WanPipeline":
+                # WAN2.2 text-to-video generation
+                output = self.pipe(**kwargs)
+                frames = output.frames[0]  # WAN2.2 returns frames in this format
+            elif self.PipelineType == "WanImageToVideoPipeline":
+                # WAN2.2 image-to-video generation
+                if request.start_image:
+                    # Load and resize the input image according to WAN2.2 requirements
+                    image = load_image(request.start_image)
+                    # Use request dimensions or defaults, but respect WAN2.2 constraints
+                    request_height = request.height if request.height > 0 else 480
+                    request_width = request.width if request.width > 0 else 832
+                    max_area = request_height * request_width
+                    aspect_ratio = image.height / image.width
+                    mod_value = self.pipe.vae_scale_factor_spatial * self.pipe.transformer.config.patch_size[1]
+                    height = round((max_area * aspect_ratio) ** 0.5 / mod_value) * mod_value
+                    width = round((max_area / aspect_ratio) ** 0.5 / mod_value) * mod_value
+                    image = image.resize((width, height))
+                    kwargs["image"] = image
+                    kwargs["height"] = height
+                    kwargs["width"] = width
+                
+                output = self.pipe(**kwargs)
+                frames = output.frames[0]
+            elif self.img2vid:
+                # Generic image-to-video generation
+                if request.start_image:
+                    image = load_image(request.start_image)
+                    image = image.resize((request.width if request.width > 0 else 1024, 
+                                       request.height if request.height > 0 else 576))
+                    kwargs["image"] = image
+                
+                output = self.pipe(**kwargs)
+                frames = output.frames[0]
+            elif self.txt2vid:
+                # Generic text-to-video generation
+                output = self.pipe(**kwargs)
+                frames = output.frames[0]
+            else:
+                return backend_pb2.Result(success=False, message=f"Pipeline {self.PipelineType} does not support video generation")
+
+            # Export video
+            export_to_video(frames, request.dst, fps=fps)
+            
+            return backend_pb2.Result(message="Video generated successfully", success=True)
+
+        except Exception as err:
+            print(f"Error generating video: {err}", file=sys.stderr)
+            traceback.print_exc()
+            return backend_pb2.Result(success=False, message=f"Error generating video: {err}")
+
 
 def serve(address):
     server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS),

backend/python/diffusers/requirements-cpu.txt

@@ -1,9 +1,12 @@
-diffusers
+--extra-index-url https://download.pytorch.org/whl/cpu
+git+https://github.com/huggingface/diffusers
 opencv-python
 transformers
+torchvision==0.22.1
 accelerate
 compel
 peft
 sentencepiece
-torch==2.4.1
-optimum-quanto
+torch==2.7.1
+optimum-quanto
+ftfy

backend/python/diffusers/requirements-cublas11.txt

@@ -1,10 +1,12 @@
 --extra-index-url https://download.pytorch.org/whl/cu118
-torch==2.4.1+cu118
-diffusers
+git+https://github.com/huggingface/diffusers
 opencv-python
 transformers
+torchvision==0.22.1
 accelerate
 compel
 peft
 sentencepiece
-optimum-quanto
+torch==2.7.1
+optimum-quanto
+ftfy

backend/python/diffusers/requirements-cublas12.txt

@@ -1,9 +1,12 @@
-torch==2.4.1
-diffusers
+--extra-index-url https://download.pytorch.org/whl/cu121
+git+https://github.com/huggingface/diffusers
 opencv-python
 transformers
+torchvision
 accelerate
 compel
 peft
 sentencepiece
-optimum-quanto
+torch
+ftfy
+optimum-quanto

backend/python/diffusers/requirements-hipblas.txt

@@ -1,11 +1,12 @@
---extra-index-url https://download.pytorch.org/whl/rocm6.0
-torch==2.3.1+rocm6.0
-torchvision==0.18.1+rocm6.0
-diffusers
+--extra-index-url https://download.pytorch.org/whl/rocm6.3
+torch==2.7.1+rocm6.3
+torchvision==0.22.1+rocm6.3
+git+https://github.com/huggingface/diffusers
 opencv-python
 transformers
 accelerate
 compel
 peft
 sentencepiece
-optimum-quanto
+optimum-quanto
+ftfy

backend/python/diffusers/requirements-intel.txt

@@ -1,15 +1,16 @@
 --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
-torchvision==0.18.1+cxx11.abi
-oneccl_bind_pt==2.3.100+xpu
+torch==2.5.1+cxx11.abi
+torchvision==0.20.1+cxx11.abi
+oneccl_bind_pt==2.8.0+xpu
 optimum[openvino]
 setuptools
-diffusers
+git+https://github.com/huggingface/diffusers
 opencv-python
 transformers
 accelerate
 compel
 peft
 sentencepiece
-optimum-quanto
+optimum-quanto
+ftfy