mirror of
https://github.com/mudler/LocalAI.git
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feat: add distributed mode (#9124)
* feat: add distributed mode (experimental) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix data races, mutexes, transactions Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix events and tool stream in agent chat Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * use ginkgo Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(cron): compute correctly time boundaries avoiding re-triggering Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not flood of healthy checks Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * do not list obvious backends as text backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * tests fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring and consolidation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Drop redundant healthcheck Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * enhancements, refactorings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This commit is contained in:
Ettore Di Giacinto
committed by
GitHub
GitHub
parent
4c870288d9
commit
59108fbe32
2
.github/gallery-agent/agent.go
vendored
2
.github/gallery-agent/agent.go
vendored
@@ -406,7 +406,7 @@ func getHuggingFaceAvatarURL(author string) string {
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}
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// Parse the response to get avatar URL
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var userInfo map[string]interface{}
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var userInfo map[string]any
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body, err := io.ReadAll(resp.Body)
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if err != nil {
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return ""
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40
.github/gallery-agent/testing.go
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40
.github/gallery-agent/testing.go
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@@ -3,7 +3,7 @@ package main
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import (
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"context"
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"fmt"
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"math/rand"
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"math/rand/v2"
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"strings"
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"time"
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)
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@@ -13,11 +13,11 @@ func runSyntheticMode() error {
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generator := NewSyntheticDataGenerator()
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// Generate a random number of synthetic models (1-3)
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numModels := generator.rand.Intn(3) + 1
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numModels := generator.rand.IntN(3) + 1
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fmt.Printf("Generating %d synthetic models for testing...\n", numModels)
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var models []ProcessedModel
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for i := 0; i < numModels; i++ {
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for i := range numModels {
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model := generator.GenerateProcessedModel()
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models = append(models, model)
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fmt.Printf("Generated synthetic model: %s\n", model.ModelID)
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@@ -42,14 +42,14 @@ type SyntheticDataGenerator struct {
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// NewSyntheticDataGenerator creates a new synthetic data generator
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func NewSyntheticDataGenerator() *SyntheticDataGenerator {
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return &SyntheticDataGenerator{
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rand: rand.New(rand.NewSource(time.Now().UnixNano())),
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rand: rand.New(rand.NewPCG(uint64(time.Now().UnixNano()), 0)),
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}
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}
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// GenerateProcessedModelFile creates a synthetic ProcessedModelFile
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func (g *SyntheticDataGenerator) GenerateProcessedModelFile() ProcessedModelFile {
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fileTypes := []string{"model", "readme", "other"}
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fileType := fileTypes[g.rand.Intn(len(fileTypes))]
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fileType := fileTypes[g.rand.IntN(len(fileTypes))]
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var path string
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var isReadme bool
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@@ -68,7 +68,7 @@ func (g *SyntheticDataGenerator) GenerateProcessedModelFile() ProcessedModelFile
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return ProcessedModelFile{
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Path: path,
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Size: int64(g.rand.Intn(1000000000) + 1000000), // 1MB to 1GB
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Size: int64(g.rand.IntN(1000000000) + 1000000), // 1MB to 1GB
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SHA256: g.randomSHA256(),
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IsReadme: isReadme,
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FileType: fileType,
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@@ -80,19 +80,19 @@ func (g *SyntheticDataGenerator) GenerateProcessedModel() ProcessedModel {
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authors := []string{"microsoft", "meta", "google", "openai", "anthropic", "mistralai", "huggingface"}
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modelNames := []string{"llama", "gpt", "claude", "mistral", "gemma", "phi", "qwen", "codellama"}
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author := authors[g.rand.Intn(len(authors))]
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modelName := modelNames[g.rand.Intn(len(modelNames))]
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author := authors[g.rand.IntN(len(authors))]
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modelName := modelNames[g.rand.IntN(len(modelNames))]
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modelID := fmt.Sprintf("%s/%s-%s", author, modelName, g.randomString(6))
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// Generate files
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numFiles := g.rand.Intn(5) + 2 // 2-6 files
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numFiles := g.rand.IntN(5) + 2 // 2-6 files
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files := make([]ProcessedModelFile, numFiles)
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// Ensure at least one model file and one readme
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hasModelFile := false
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hasReadme := false
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for i := 0; i < numFiles; i++ {
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for i := range numFiles {
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files[i] = g.GenerateProcessedModelFile()
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if files[i].FileType == "model" {
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hasModelFile = true
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@@ -140,27 +140,27 @@ func (g *SyntheticDataGenerator) GenerateProcessedModel() ProcessedModel {
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// Generate sample metadata
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licenses := []string{"apache-2.0", "mit", "llama2", "gpl-3.0", "bsd", ""}
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license := licenses[g.rand.Intn(len(licenses))]
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license := licenses[g.rand.IntN(len(licenses))]
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sampleTags := []string{"llm", "gguf", "gpu", "cpu", "text-to-text", "chat", "instruction-tuned"}
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numTags := g.rand.Intn(4) + 3 // 3-6 tags
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numTags := g.rand.IntN(4) + 3 // 3-6 tags
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tags := make([]string, numTags)
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for i := 0; i < numTags; i++ {
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tags[i] = sampleTags[g.rand.Intn(len(sampleTags))]
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for i := range numTags {
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tags[i] = sampleTags[g.rand.IntN(len(sampleTags))]
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}
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// Remove duplicates
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tags = g.removeDuplicates(tags)
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// Optionally include icon (50% chance)
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icon := ""
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if g.rand.Intn(2) == 0 {
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if g.rand.IntN(2) == 0 {
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icon = fmt.Sprintf("https://cdn-avatars.huggingface.co/v1/production/uploads/%s.png", g.randomString(24))
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}
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return ProcessedModel{
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ModelID: modelID,
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Author: author,
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Downloads: g.rand.Intn(1000000) + 1000,
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Downloads: g.rand.IntN(1000000) + 1000,
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LastModified: g.randomDate(),
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Files: files,
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PreferredModelFile: preferredModelFile,
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@@ -180,7 +180,7 @@ func (g *SyntheticDataGenerator) randomString(length int) string {
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const charset = "abcdefghijklmnopqrstuvwxyz0123456789"
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b := make([]byte, length)
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for i := range b {
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b[i] = charset[g.rand.Intn(len(charset))]
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b[i] = charset[g.rand.IntN(len(charset))]
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}
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return string(b)
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}
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@@ -189,14 +189,14 @@ func (g *SyntheticDataGenerator) randomSHA256() string {
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const charset = "0123456789abcdef"
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b := make([]byte, 64)
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for i := range b {
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b[i] = charset[g.rand.Intn(len(charset))]
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b[i] = charset[g.rand.IntN(len(charset))]
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}
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return string(b)
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}
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func (g *SyntheticDataGenerator) randomDate() string {
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now := time.Now()
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daysAgo := g.rand.Intn(365) // Random date within last year
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daysAgo := g.rand.IntN(365) // Random date within last year
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pastDate := now.AddDate(0, 0, -daysAgo)
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return pastDate.Format("2006-01-02T15:04:05.000Z")
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}
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@@ -220,5 +220,5 @@ func (g *SyntheticDataGenerator) generateReadmeContent(modelName, author string)
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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),
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}
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return templates[g.rand.Intn(len(templates))]
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return templates[g.rand.IntN(len(templates))]
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}
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4
.github/workflows/test.yml
vendored
4
.github/workflows/test.yml
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@@ -21,7 +21,7 @@ jobs:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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go-version: ['1.25.x']
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go-version: ['1.26.x']
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steps:
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- name: Free Disk Space (Ubuntu)
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uses: jlumbroso/free-disk-space@main
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@@ -179,7 +179,7 @@ jobs:
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runs-on: macos-latest
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strategy:
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matrix:
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go-version: ['1.25.x']
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go-version: ['1.26.x']
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steps:
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- name: Clone
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uses: actions/checkout@v6
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