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Merge pull request #1 from rfc1437/session-cache-upgrade-phase1

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This commit is contained in:
Georg Bauer
2026-03-21 13:35:53 +01:00
committed by GitHub
parent 41199cb9bc 491a1e6ffe
commit 8ebf19408b
50 changed files with 8322 additions and 1621 deletions
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6
.vscode/settings.json vendored Normal file
View File

@@ -0,0 +1,6 @@
{
"chat.tools.terminal.autoApprove": {
"./test.sh": true,
"setopt": true
}
}

15
AGENTS.md
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@@ -6,10 +6,20 @@ Native macOS SwiftUI app for local LLMs on Apple Silicon via MLX. Provides a cha
**Always use `./build.sh` to build the project** — never call `xcodebuild` directly. The script runs xcodegen first (to pick up new/removed files) and uses the correct scheme, destination, and build directory. **Always use `./build.sh` to build the project** — never call `xcodebuild` directly. The script runs xcodegen first (to pick up new/removed files) and uses the correct scheme, destination, and build directory.
**Always use `./test.sh` to run tests** — it regenerates the Xcode project first and runs the shared `MLXServer` test scheme so test runs are reproducible.
Tests are required for finished work when the change is reasonably testable.
Relevant tests must exist and must pass before work is considered complete.
Pre-existing errors don't exist: every error is your responsibility and you have to fix it before claiming you are done.
```bash ```bash
# Build (requires xcodegen: brew install xcodegen) # Build (requires xcodegen: brew install xcodegen)
./build.sh ./build.sh
# Test
./test.sh
# Run # Run
open "build/Debug/MLX Server.app" open "build/Debug/MLX Server.app"
``` ```
@@ -42,8 +52,9 @@ open "build/Debug/MLX Server.app"
| Alias | HuggingFace ID | Notes | | Alias | HuggingFace ID | Notes |
|-------|---------------|-------| |-------|---------------|-------|
| `gemma` | `mlx-community/gemma-3-4b-it-4bit` | Vision + tool use via `tool_code` blocks (128k context) | | `gemma` | `mlx-community/gemma-3-4b-it-4bit` | Vision + tool use via `tool_code` blocks (128k context) |
| `qwen` | `mlx-community/Qwen3-VL-4B-Instruct-4bit` | Vision + tool use via `<tool_call>` tags (256k context) | | `qwen` | `mlx-community/Qwen3.5-4B-MLX-4bit` | Vision + thinking mode + tool use via `<tool_call>` tags (256k context) |
| `qwen3.5-9b` | `mlx-community/Qwen3.5-9B-4bit` | Thinking mode, tool use (256k context) | | `qwen3.5-0.8b` | `mlx-community/Qwen3.5-0.8B-4bit` | Vision + thinking mode + tool use via `<tool_call>` tags (256k context) |
| `qwen3.5-9b` | `mlx-community/Qwen3.5-9B-4bit` | Vision + thinking mode + tool use via `<tool_call>` tags (256k context) |
Any model in MLX format on HuggingFace can be added — no restriction on uploader or architecture. Any model in MLX format on HuggingFace can be added — no restriction on uploader or architecture.

201
MLXServer.xcodeproj/project.pbxproj
View File

@@ -9,14 +9,19 @@
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@@ -25,12 +30,24 @@
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@@ -246,6 +340,24 @@
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@@ -276,6 +388,7 @@
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50B6861FF8610B3ED4FFAD9D /* MLXServerApp.swift in Sources */, 50B6861FF8610B3ED4FFAD9D /* MLXServerApp.swift in Sources */,
@@ -320,6 +459,7 @@
2CAAF7129F7CC45200FA9F6B /* ModelPickerView.swift in Sources */, 2CAAF7129F7CC45200FA9F6B /* ModelPickerView.swift in Sources */,
B1D9BC407DB7DB1489230C20 /* MonitorView.swift in Sources */, B1D9BC407DB7DB1489230C20 /* MonitorView.swift in Sources */,
165E8AB6ADAE1D59B1A86420 /* Preferences.swift in Sources */, 165E8AB6ADAE1D59B1A86420 /* Preferences.swift in Sources */,
AA17474A72C7F4EFBD5C4925 /* PromptBuilder.swift in Sources */,
4158FA884D981D73288FB74C /* SaveChatCommands.swift in Sources */, 4158FA884D981D73288FB74C /* SaveChatCommands.swift in Sources */,
07119250A7F9D6ECE7F6B8FD /* SceneCommands.swift in Sources */, 07119250A7F9D6ECE7F6B8FD /* SceneCommands.swift in Sources */,
20FFB5DBF75AA6C359AAE31C /* SceneManagementView.swift in Sources */, 20FFB5DBF75AA6C359AAE31C /* SceneManagementView.swift in Sources */,
@@ -328,6 +468,8 @@
CFEE79815DFB80E51FE3745A /* SceneStore.swift in Sources */, CFEE79815DFB80E51FE3745A /* SceneStore.swift in Sources */,
D666A311788375E8A061C832 /* SettingsView.swift in Sources */, D666A311788375E8A061C832 /* SettingsView.swift in Sources */,
621B7E4382199AC1378F5F9C /* StatusBarView.swift in Sources */, 621B7E4382199AC1378F5F9C /* StatusBarView.swift in Sources */,
67262C5E24739F1FE0011439 /* StreamingSSEEncoder.swift in Sources */,
741692862DB1F13EA0B2D14D /* TokenPrefixCache.swift in Sources */,
189362AAE2CDE5D4B3428334 /* ToolCallParser.swift in Sources */, 189362AAE2CDE5D4B3428334 /* ToolCallParser.swift in Sources */,
84D32315B418B5243E017350 /* ToolPromptBuilder.swift in Sources */, 84D32315B418B5243E017350 /* ToolPromptBuilder.swift in Sources */,
); );
@@ -335,7 +477,49 @@
}; };
/* End PBXSourcesBuildPhase section */ /* End PBXSourcesBuildPhase section */
/* Begin PBXTargetDependency section */
8870DD8F1917C831FD4FD595 /* PBXTargetDependency */ = {
isa = PBXTargetDependency;
target = BCD7107EE884C9B2F4C2C40E /* MLXServer */;
targetProxy = 9F9E4F692B655CD8CE88479C /* PBXContainerItemProxy */;
};
/* End PBXTargetDependency section */
/* Begin XCBuildConfiguration section */ /* Begin XCBuildConfiguration section */
18921C5B777D8B7FEF662D6F /* Release */ = {
isa = XCBuildConfiguration;
buildSettings = {
BUNDLE_LOADER = "$(TEST_HOST)";
COMBINE_HIDPI_IMAGES = YES;
GENERATE_INFOPLIST_FILE = YES;
LD_RUNPATH_SEARCH_PATHS = (
"$(inherited)",
"@executable_path/../Frameworks",
"@loader_path/../Frameworks",
);
PRODUCT_BUNDLE_IDENTIFIER = com.mlxserver.MLXServerTests;
SDKROOT = macosx;
TEST_HOST = "$(BUILT_PRODUCTS_DIR)/MLX Server.app/Contents/MacOS/MLX Server";
};
name = Release;
};
2B83417701A93BF554428C56 /* Debug */ = {
isa = XCBuildConfiguration;
buildSettings = {
BUNDLE_LOADER = "$(TEST_HOST)";
COMBINE_HIDPI_IMAGES = YES;
GENERATE_INFOPLIST_FILE = YES;
LD_RUNPATH_SEARCH_PATHS = (
"$(inherited)",
"@executable_path/../Frameworks",
"@loader_path/../Frameworks",
);
PRODUCT_BUNDLE_IDENTIFIER = com.mlxserver.MLXServerTests;
SDKROOT = macosx;
TEST_HOST = "$(BUILT_PRODUCTS_DIR)/MLX Server.app/Contents/MacOS/MLX Server";
};
name = Debug;
};
6C0C08FC4653A138A768ECF0 /* Release */ = { 6C0C08FC4653A138A768ECF0 /* Release */ = {
isa = XCBuildConfiguration; isa = XCBuildConfiguration;
buildSettings = { buildSettings = {
@@ -524,6 +708,15 @@
defaultConfigurationIsVisible = 0; defaultConfigurationIsVisible = 0;
defaultConfigurationName = Debug; defaultConfigurationName = Debug;
}; };
A2168D037766ED36A199C6F7 /* Build configuration list for PBXNativeTarget "MLXServerTests" */ = {
isa = XCConfigurationList;
buildConfigurations = (
2B83417701A93BF554428C56 /* Debug */,
18921C5B777D8B7FEF662D6F /* Release */,
);
defaultConfigurationIsVisible = 0;
defaultConfigurationName = Debug;
};
/* End XCConfigurationList section */ /* End XCConfigurationList section */
/* Begin XCRemoteSwiftPackageReference section */ /* Begin XCRemoteSwiftPackageReference section */

116
MLXServer.xcodeproj/xcshareddata/xcschemes/MLXServer.xcscheme Normal file
View File

@@ -0,0 +1,116 @@
<?xml version="1.0" encoding="UTF-8"?>
<Scheme
LastUpgradeVersion = "1640"
version = "1.7">
<BuildAction
parallelizeBuildables = "YES"
buildImplicitDependencies = "YES"
runPostActionsOnFailure = "NO">
<BuildActionEntries>
<BuildActionEntry
buildForTesting = "YES"
buildForRunning = "YES"
buildForProfiling = "YES"
buildForArchiving = "YES"
buildForAnalyzing = "YES">
<BuildableReference
BuildableIdentifier = "primary"
BlueprintIdentifier = "BCD7107EE884C9B2F4C2C40E"
BuildableName = "MLXServer.app"
BlueprintName = "MLXServer"
ReferencedContainer = "container:MLXServer.xcodeproj">
</BuildableReference>
</BuildActionEntry>
<BuildActionEntry
buildForTesting = "YES"
buildForRunning = "NO"
buildForProfiling = "NO"
buildForArchiving = "NO"
buildForAnalyzing = "NO">
<BuildableReference
BuildableIdentifier = "primary"
BlueprintIdentifier = "CE11F8C258BB944F38A5840D"
BuildableName = "MLXServerTests.xctest"
BlueprintName = "MLXServerTests"
ReferencedContainer = "container:MLXServer.xcodeproj">
</BuildableReference>
</BuildActionEntry>
</BuildActionEntries>
</BuildAction>
<TestAction
buildConfiguration = "Debug"
selectedDebuggerIdentifier = "Xcode.DebuggerFoundation.Debugger.LLDB"
selectedLauncherIdentifier = "Xcode.DebuggerFoundation.Launcher.LLDB"
shouldUseLaunchSchemeArgsEnv = "YES"
onlyGenerateCoverageForSpecifiedTargets = "NO">
<MacroExpansion>
<BuildableReference
BuildableIdentifier = "primary"
BlueprintIdentifier = "BCD7107EE884C9B2F4C2C40E"
BuildableName = "MLXServer.app"
BlueprintName = "MLXServer"
ReferencedContainer = "container:MLXServer.xcodeproj">
</BuildableReference>
</MacroExpansion>
<Testables>
<TestableReference
skipped = "NO"
parallelizable = "NO">
<BuildableReference
BuildableIdentifier = "primary"
BlueprintIdentifier = "CE11F8C258BB944F38A5840D"
BuildableName = "MLXServerTests.xctest"
BlueprintName = "MLXServerTests"
ReferencedContainer = "container:MLXServer.xcodeproj">
</BuildableReference>
</TestableReference>
</Testables>
<CommandLineArguments>
</CommandLineArguments>
</TestAction>
<LaunchAction
buildConfiguration = "Debug"
selectedDebuggerIdentifier = "Xcode.DebuggerFoundation.Debugger.LLDB"
selectedLauncherIdentifier = "Xcode.DebuggerFoundation.Launcher.LLDB"
launchStyle = "0"
useCustomWorkingDirectory = "NO"
ignoresPersistentStateOnLaunch = "NO"
debugDocumentVersioning = "YES"
debugServiceExtension = "internal"
allowLocationSimulation = "YES">
<BuildableProductRunnable
runnableDebuggingMode = "0">
<BuildableReference
BuildableIdentifier = "primary"
BlueprintIdentifier = "BCD7107EE884C9B2F4C2C40E"
BuildableName = "MLXServer.app"
BlueprintName = "MLXServer"
ReferencedContainer = "container:MLXServer.xcodeproj">
</BuildableReference>
</BuildableProductRunnable>
</LaunchAction>
<ProfileAction
buildConfiguration = "Release"
shouldUseLaunchSchemeArgsEnv = "YES"
savedToolIdentifier = ""
useCustomWorkingDirectory = "NO"
debugDocumentVersioning = "YES">
<BuildableProductRunnable
runnableDebuggingMode = "0">
<BuildableReference
BuildableIdentifier = "primary"
BlueprintIdentifier = "BCD7107EE884C9B2F4C2C40E"
BuildableName = "MLXServer.app"
BlueprintName = "MLXServer"
ReferencedContainer = "container:MLXServer.xcodeproj">
</BuildableReference>
</BuildableProductRunnable>
</ProfileAction>
<AnalyzeAction
buildConfiguration = "Debug">
</AnalyzeAction>
<ArchiveAction
buildConfiguration = "Release"
revealArchiveInOrganizer = "YES">
</ArchiveAction>
</Scheme>

67
MLXServer/ContentView.swift
View File

@@ -14,6 +14,12 @@ struct ContentView: View {
@State private var exportDocument: ChatExportDocument? @State private var exportDocument: ChatExportDocument?
@State private var documentErrorMessage: String? @State private var documentErrorMessage: String?
@State private var exportErrorMessage: String? @State private var exportErrorMessage: String?
@State private var startupTask: Task<Void, Never>?
@State private var isOpeningDocument = false
private var isRunningTests: Bool {
ProcessInfo.processInfo.environment["XCTestConfigurationFilePath"] != nil
}
var body: some View { var body: some View {
exportedContent exportedContent
@@ -30,17 +36,12 @@ struct ContentView: View {
delegate.chatViewModel = vm delegate.chatViewModel = vm
} }
// Auto-start API server if configured // Auto-start API server if configured
if Preferences.apiAutoStart { if Preferences.apiAutoStart && !isRunningTests {
vm.startAPIServer() vm.startAPIServer()
} }
// Restore autosaved session if no document is being opened
if !documentController.hasPendingOpenRequests {
Task {
await vm.restoreFromAutosave()
}
}
} }
scheduleStartupWork()
processPendingOpenRequests() processPendingOpenRequests()
} }
.onChange(of: modelManager.currentModel) { .onChange(of: modelManager.currentModel) {
@@ -58,6 +59,7 @@ struct ContentView: View {
showLoadError = modelManager.errorMessage != nil showLoadError = modelManager.errorMessage != nil
} }
.onChange(of: documentController.openRequestNonce) { .onChange(of: documentController.openRequestNonce) {
startupTask?.cancel()
processPendingOpenRequests() processPendingOpenRequests()
} }
} }
@@ -372,11 +374,58 @@ struct ContentView: View {
Task { Task {
while let url = documentController.consumeNextOpenRequest() { while let url = documentController.consumeNextOpenRequest() {
startupTask?.cancel()
await openDocument(at: url) await openDocument(at: url)
} }
} }
} }
private func scheduleStartupWork() {
guard let chatVM else { return }
startupTask?.cancel()
startupTask = Task {
try? await Task.sleep(nanoseconds: 250_000_000)
guard !Task.isCancelled else { return }
if documentController.hasPendingOpenRequests {
await MainActor.run {
processPendingOpenRequests()
}
return
}
guard !isOpeningDocument else { return }
if !isRunningTests, ChatViewModel.hasAutosavedSession {
let restored = await chatVM.restoreFromAutosave()
guard !Task.isCancelled else { return }
guard !isOpeningDocument else { return }
if restored || documentController.hasPendingOpenRequests {
await MainActor.run {
processPendingOpenRequests()
}
return
}
}
guard !Task.isCancelled else { return }
guard !isOpeningDocument else { return }
guard !documentController.hasPendingOpenRequests else {
await MainActor.run {
processPendingOpenRequests()
}
return
}
guard modelManager.currentModel == nil else { return }
let modelId = Preferences.defaultModelId ?? Preferences.lastModelId ?? ModelConfig.default.id
if let config = ModelConfig.availableModels.first(where: { $0.id == modelId }) {
await modelManager.loadModel(config)
}
}
}
private func openDocument(at url: URL, skipUnsavedCheck: Bool = false) async { private func openDocument(at url: URL, skipUnsavedCheck: Bool = false) async {
if !skipUnsavedCheck { if !skipUnsavedCheck {
let shouldContinue = confirmDiscardUnsavedChanges( let shouldContinue = confirmDiscardUnsavedChanges(
@@ -386,6 +435,10 @@ struct ContentView: View {
guard shouldContinue else { return } guard shouldContinue else { return }
} }
startupTask?.cancel()
isOpeningDocument = true
defer { isOpeningDocument = false }
do { do {
try await chatVM?.loadDocument(from: url) try await chatVM?.loadDocument(from: url)
} catch { } catch {

65
MLXServer/Documents/ChatDocumentManifest.swift
View File

@@ -11,7 +11,7 @@ struct ChatDocumentManifest: Codable {
var messages: [StoredChatMessage] var messages: [StoredChatMessage]
var uiState: StoredChatUIState var uiState: StoredChatUIState
static let currentSchemaVersion = 1 static let currentSchemaVersion = 2
struct StoredModelInfo: Codable, Hashable { struct StoredModelInfo: Codable, Hashable {
var id: String var id: String
@@ -23,6 +23,69 @@ struct ChatDocumentManifest: Codable {
var systemPrompt: String var systemPrompt: String
var thinkingEnabled: Bool var thinkingEnabled: Bool
var temperature: Double var temperature: Double
var topP: Double
var topK: Int
var minP: Double
var maxTokens: Int
var repetitionPenalty: Double?
var presencePenalty: Double?
var frequencyPenalty: Double?
init(systemPrompt: String, generationSettings: GenerationSettings) {
self.systemPrompt = systemPrompt
self.thinkingEnabled = generationSettings.thinkingEnabled
self.temperature = generationSettings.temperature
self.topP = generationSettings.topP
self.topK = generationSettings.topK
self.minP = generationSettings.minP
self.maxTokens = generationSettings.maxTokens
self.repetitionPenalty = generationSettings.repetitionPenalty
self.presencePenalty = generationSettings.presencePenalty
self.frequencyPenalty = generationSettings.frequencyPenalty
}
var generationSettings: GenerationSettings {
GenerationSettings(
temperature: temperature,
topP: topP,
topK: topK,
minP: minP,
maxTokens: maxTokens,
repetitionPenalty: repetitionPenalty,
presencePenalty: presencePenalty,
frequencyPenalty: frequencyPenalty,
thinkingEnabled: thinkingEnabled
).normalized()
}
private enum CodingKeys: String, CodingKey {
case systemPrompt
case thinkingEnabled
case temperature
case topP
case topK
case minP
case maxTokens
case repetitionPenalty
case presencePenalty
case frequencyPenalty
}
init(from decoder: Decoder) throws {
let container = try decoder.container(keyedBy: CodingKeys.self)
let fallback = GenerationSettings()
systemPrompt = try container.decodeIfPresent(String.self, forKey: .systemPrompt) ?? ""
thinkingEnabled = try container.decodeIfPresent(Bool.self, forKey: .thinkingEnabled) ?? fallback.thinkingEnabled
temperature = try container.decodeIfPresent(Double.self, forKey: .temperature) ?? fallback.temperature
topP = try container.decodeIfPresent(Double.self, forKey: .topP) ?? fallback.topP
topK = try container.decodeIfPresent(Int.self, forKey: .topK) ?? fallback.topK
minP = try container.decodeIfPresent(Double.self, forKey: .minP) ?? fallback.minP
maxTokens = try container.decodeIfPresent(Int.self, forKey: .maxTokens) ?? fallback.maxTokens
repetitionPenalty = try container.decodeIfPresent(Double.self, forKey: .repetitionPenalty)
presencePenalty = try container.decodeIfPresent(Double.self, forKey: .presencePenalty)
frequencyPenalty = try container.decodeIfPresent(Double.self, forKey: .frequencyPenalty)
}
} }
struct StoredChatUIState: Codable, Hashable { struct StoredChatUIState: Codable, Hashable {

2
MLXServer/Documents/ChatDocumentMigration.swift
View File

@@ -12,6 +12,8 @@ enum ChatDocumentMigration {
switch envelope.schemaVersion { switch envelope.schemaVersion {
case 1: case 1:
return try decoder.decode(ChatDocumentManifest.self, from: data) return try decoder.decode(ChatDocumentManifest.self, from: data)
case 2:
return try decoder.decode(ChatDocumentManifest.self, from: data)
default: default:
throw ChatDocumentError.unsupportedSchemaVersion(envelope.schemaVersion) throw ChatDocumentError.unsupportedSchemaVersion(envelope.schemaVersion)
} }

24
MLXServer/MLXServerApp.swift
View File

@@ -4,11 +4,26 @@ import MLX
@MainActor @MainActor
final class AppDelegate: NSObject, NSApplicationDelegate { final class AppDelegate: NSObject, NSApplicationDelegate {
var chatViewModel: ChatViewModel? var chatViewModel: ChatViewModel?
private var terminationTask: Task<Void, Never>?
func application(_ application: NSApplication, open urls: [URL]) { func application(_ application: NSApplication, open urls: [URL]) {
ChatDocumentController.shared.enqueueOpenRequests(urls) ChatDocumentController.shared.enqueueOpenRequests(urls)
} }
func applicationShouldTerminate(_ sender: NSApplication) -> NSApplication.TerminateReply {
if terminationTask != nil {
return .terminateLater
}
terminationTask = Task { @MainActor [weak self] in
await self?.chatViewModel?.prepareForTermination()
sender.reply(toApplicationShouldTerminate: true)
self?.terminationTask = nil
}
return .terminateLater
}
func applicationWillTerminate(_ notification: Notification) { func applicationWillTerminate(_ notification: Notification) {
chatViewModel?.autosaveToSandbox() chatViewModel?.autosaveToSandbox()
} }
@@ -31,15 +46,6 @@ struct MLXServerApp: App {
.environment(documentController) .environment(documentController)
.environment(modelManager) .environment(modelManager)
.environment(sceneStore) .environment(sceneStore)
.task {
guard !documentController.hasPendingOpenRequests else { return }
guard !ChatViewModel.hasAutosavedSession else { return }
// Auto-load: configured default → last used → built-in default
let modelId = Preferences.defaultModelId ?? Preferences.lastModelId ?? ModelConfig.default.id
if let config = ModelConfig.availableModels.first(where: { $0.id == modelId }) {
await modelManager.loadModel(config)
}
}
} }
.windowStyle(.titleBar) .windowStyle(.titleBar)
.defaultSize(width: 800, height: 700) .defaultSize(width: 800, height: 700)

24
MLXServer/Models/ChatScene.swift
View File

@@ -6,19 +6,41 @@ struct ChatScene: Codable, Identifiable, Hashable {
var modelId: String? var modelId: String?
var systemPrompt: String var systemPrompt: String
var starterPrompt: String var starterPrompt: String
var generationOverrides: GenerationSettingsOverride
init( init(
id: UUID = UUID(), id: UUID = UUID(),
name: String, name: String,
modelId: String? = nil, modelId: String? = nil,
systemPrompt: String = "", systemPrompt: String = "",
starterPrompt: String = "" starterPrompt: String = "",
generationOverrides: GenerationSettingsOverride = .none
) { ) {
self.id = id self.id = id
self.name = name self.name = name
self.modelId = modelId self.modelId = modelId
self.systemPrompt = systemPrompt self.systemPrompt = systemPrompt
self.starterPrompt = starterPrompt self.starterPrompt = starterPrompt
self.generationOverrides = generationOverrides
}
private enum CodingKeys: String, CodingKey {
case id
case name
case modelId
case systemPrompt
case starterPrompt
case generationOverrides
}
init(from decoder: Decoder) throws {
let container = try decoder.container(keyedBy: CodingKeys.self)
id = try container.decode(UUID.self, forKey: .id)
name = try container.decode(String.self, forKey: .name)
modelId = try container.decodeIfPresent(String.self, forKey: .modelId)
systemPrompt = try container.decodeIfPresent(String.self, forKey: .systemPrompt) ?? ""
starterPrompt = try container.decodeIfPresent(String.self, forKey: .starterPrompt) ?? ""
generationOverrides = try container.decodeIfPresent(GenerationSettingsOverride.self, forKey: .generationOverrides) ?? .none
} }
var trimmedName: String { var trimmedName: String {

157
MLXServer/Models/GenerationSettings.swift Normal file
View File

@@ -0,0 +1,157 @@
import Foundation
struct GenerationSettings: Codable, Hashable, Sendable {
var temperature: Double
var topP: Double
var topK: Int
var minP: Double
var maxTokens: Int
var repetitionPenalty: Double?
var presencePenalty: Double?
var frequencyPenalty: Double?
var thinkingEnabled: Bool
init(
temperature: Double = 0.7,
topP: Double = 1.0,
topK: Int = 0,
minP: Double = 0.0,
maxTokens: Int = 4096,
repetitionPenalty: Double? = nil,
presencePenalty: Double? = nil,
frequencyPenalty: Double? = nil,
thinkingEnabled: Bool = true
) {
self.temperature = temperature
self.topP = topP
self.topK = topK
self.minP = minP
self.maxTokens = maxTokens
self.repetitionPenalty = repetitionPenalty
self.presencePenalty = presencePenalty
self.frequencyPenalty = frequencyPenalty
self.thinkingEnabled = thinkingEnabled
}
func normalized() -> GenerationSettings {
GenerationSettings(
temperature: max(0, temperature),
topP: min(max(topP, 0), 1),
topK: max(0, topK),
minP: min(max(minP, 0), 1),
maxTokens: max(1, maxTokens),
repetitionPenalty: Self.normalizePositive(repetitionPenalty),
presencePenalty: Self.normalizeSignedPenalty(presencePenalty),
frequencyPenalty: Self.normalizeSignedPenalty(frequencyPenalty),
thinkingEnabled: thinkingEnabled
)
}
func applying(_ overrides: GenerationSettingsOverride) -> GenerationSettings {
GenerationSettings(
temperature: overrides.temperature ?? temperature,
topP: overrides.topP ?? topP,
topK: overrides.topK ?? topK,
minP: overrides.minP ?? minP,
maxTokens: overrides.maxTokens ?? maxTokens,
repetitionPenalty: overrides.repetitionPenalty ?? repetitionPenalty,
presencePenalty: overrides.presencePenalty ?? presencePenalty,
frequencyPenalty: overrides.frequencyPenalty ?? frequencyPenalty,
thinkingEnabled: overrides.thinkingEnabled ?? thinkingEnabled
)
.normalized()
}
static func modelDefault(for modelId: String, legacyThinkingEnabled: Bool = true) -> GenerationSettings {
let fallback = ModelConfig.resolve(modelId)?.defaultGenerationSettings ?? .generalDefault
var resolved = fallback
if !legacyThinkingEnabled {
resolved.thinkingEnabled = false
}
return resolved.normalized()
}
static let generalDefault = GenerationSettings()
static let technicalDefault = GenerationSettings(
temperature: 0.35,
topP: 0.9,
topK: 40,
minP: 0.0,
maxTokens: 4096,
repetitionPenalty: 1.05,
presencePenalty: nil,
frequencyPenalty: nil,
thinkingEnabled: true
)
static let roleplayDefault = GenerationSettings(
temperature: 0.85,
topP: 0.95,
topK: 60,
minP: 0.0,
maxTokens: 4096,
repetitionPenalty: 1.02,
presencePenalty: nil,
frequencyPenalty: nil,
thinkingEnabled: false
)
private static func normalizePositive(_ value: Double?) -> Double? {
guard let value else { return nil }
return value > 0 ? value : nil
}
private static func normalizeSignedPenalty(_ value: Double?) -> Double? {
guard let value else { return nil }
return min(max(value, -2), 2)
}
}
struct GenerationSettingsOverride: Codable, Hashable, Sendable {
var temperature: Double?
var topP: Double?
var topK: Int?
var minP: Double?
var maxTokens: Int?
var repetitionPenalty: Double?
var presencePenalty: Double?
var frequencyPenalty: Double?
var thinkingEnabled: Bool?
init(
temperature: Double? = nil,
topP: Double? = nil,
topK: Int? = nil,
minP: Double? = nil,
maxTokens: Int? = nil,
repetitionPenalty: Double? = nil,
presencePenalty: Double? = nil,
frequencyPenalty: Double? = nil,
thinkingEnabled: Bool? = nil
) {
self.temperature = temperature
self.topP = topP
self.topK = topK
self.minP = minP
self.maxTokens = maxTokens
self.repetitionPenalty = repetitionPenalty
self.presencePenalty = presencePenalty
self.frequencyPenalty = frequencyPenalty
self.thinkingEnabled = thinkingEnabled
}
static let none = GenerationSettingsOverride()
var hasOverrides: Bool {
temperature != nil
|| topP != nil
|| topK != nil
|| minP != nil
|| maxTokens != nil
|| repetitionPenalty != nil
|| presencePenalty != nil
|| frequencyPenalty != nil
|| thinkingEnabled != nil
}
}

345
MLXServer/Models/InferenceStats.swift
View File

@@ -20,19 +20,29 @@ final class LiveCounters: @unchecked Sendable {
private var _promptTokens: Int = 0 private var _promptTokens: Int = 0
private var _generationTokens: Int = 0 private var _generationTokens: Int = 0
private var _tokensPerSecond: Double = 0 private var _tokensPerSecond: Double = 0
private var _prefillTokensPerSecond: Double = 0
private var _timeToFirstToken: TimeInterval = 0
private var _isPrefilling: Bool = false private var _isPrefilling: Bool = false
private var _isGenerating: Bool = false private var _isGenerating: Bool = false
private var _contextMax: Int = 0 private var _contextMax: Int = 0
private var _currentPhaseElapsed: TimeInterval = 0 private var _currentPhaseElapsed: TimeInterval = 0
private var _currentCacheMatchedPromptTokens: Int = 0
private var _currentCacheRebuiltPromptTokens: Int = 0
private var _cacheMatchDepth: Int = 0
private var _visionEncoderTime: TimeInterval = 0
// Cumulative // Cumulative
private var _totalRequests: Int = 0 private var _totalRequests: Int = 0
private var _totalPromptTokens: Int = 0 private var _totalPromptTokens: Int = 0
private var _totalGenerationTokens: Int = 0 private var _totalGenerationTokens: Int = 0
private var _totalCacheReusePromptTokens: Int = 0
private var _totalCacheRebuildPromptTokens: Int = 0
private var _totalPreparingDuration: TimeInterval = 0 private var _totalPreparingDuration: TimeInterval = 0
private var _totalSessionBuildDuration: TimeInterval = 0 private var _totalSessionBuildDuration: TimeInterval = 0
private var _totalPrefillDuration: TimeInterval = 0 private var _totalPrefillDuration: TimeInterval = 0
private var _totalGenerationDuration: TimeInterval = 0 private var _totalGenerationDuration: TimeInterval = 0
private var _totalVisionEncoderDuration: TimeInterval = 0
private var _totalDisconnects: Int = 0
func requestStarted(requestId: String, contextLength: Int) { func requestStarted(requestId: String, contextLength: Int) {
let now = Date() let now = Date()
@@ -45,8 +55,16 @@ final class LiveCounters: @unchecked Sendable {
_promptTokens = 0 _promptTokens = 0
_generationTokens = 0 _generationTokens = 0
_tokensPerSecond = 0 _tokensPerSecond = 0
_prefillTokensPerSecond = 0
_timeToFirstToken = 0
_contextMax = contextLength _contextMax = contextLength
requestPhases[requestId] = RequestState(phase: .preparing, phaseStartedAt: now) _cacheMatchDepth = 0
_visionEncoderTime = 0
requestPhases[requestId] = RequestState(
phase: .preparing,
phaseStartedAt: now,
requestStartedAt: now
)
refreshCurrentPhaseElapsed(now: now) refreshCurrentPhaseElapsed(now: now)
lock.unlock() lock.unlock()
} }
@@ -57,9 +75,24 @@ final class LiveCounters: @unchecked Sendable {
if let current = requestPhases[requestId] { if let current = requestPhases[requestId] {
decrementCount(for: current.phase) decrementCount(for: current.phase)
accumulateDuration(for: current.phase, elapsed: now.timeIntervalSince(current.phaseStartedAt)) accumulateDuration(for: current.phase, elapsed: now.timeIntervalSince(current.phaseStartedAt))
requestPhases[requestId] = RequestState(
phase: phase,
phaseStartedAt: now,
requestStartedAt: current.requestStartedAt,
matchedPromptTokens: current.matchedPromptTokens,
rebuiltPromptTokens: current.rebuiltPromptTokens,
hasRecordedFirstToken: current.hasRecordedFirstToken,
disconnectRecorded: current.disconnectRecorded,
visionEncoderTime: current.visionEncoderTime
)
} else {
requestPhases[requestId] = RequestState(
phase: phase,
phaseStartedAt: now,
requestStartedAt: now
)
} }
incrementCount(for: phase) incrementCount(for: phase)
requestPhases[requestId] = RequestState(phase: phase, phaseStartedAt: now)
_isPrefilling = _prefillRequests > 0 || _sessionBuildRequests > 0 || _preparingRequests > 0 _isPrefilling = _prefillRequests > 0 || _sessionBuildRequests > 0 || _preparingRequests > 0
_isGenerating = _generatingRequests > 0 _isGenerating = _generatingRequests > 0
refreshCurrentPhaseElapsed(now: now) refreshCurrentPhaseElapsed(now: now)
@@ -70,11 +103,19 @@ final class LiveCounters: @unchecked Sendable {
let now = Date() let now = Date()
lock.lock() lock.lock()
if let current = requestPhases[requestId] { if let current = requestPhases[requestId] {
let prefillElapsed = max(now.timeIntervalSince(current.phaseStartedAt), 0)
_prefillTokensPerSecond = prefillElapsed > 0
? Double(promptTokens) / prefillElapsed
: 0
decrementCount(for: current.phase) decrementCount(for: current.phase)
accumulateDuration(for: current.phase, elapsed: now.timeIntervalSince(current.phaseStartedAt)) accumulateDuration(for: current.phase, elapsed: prefillElapsed)
} }
incrementCount(for: .generating) incrementCount(for: .generating)
requestPhases[requestId] = RequestState(phase: .generating, phaseStartedAt: now) if var state = requestPhases[requestId] {
state.phase = .generating
state.phaseStartedAt = now
requestPhases[requestId] = state
}
_promptTokens = promptTokens _promptTokens = promptTokens
_totalPromptTokens += promptTokens _totalPromptTokens += promptTokens
_isPrefilling = _prefillRequests > 0 || _sessionBuildRequests > 0 || _preparingRequests > 0 _isPrefilling = _prefillRequests > 0 || _sessionBuildRequests > 0 || _preparingRequests > 0
@@ -83,6 +124,20 @@ final class LiveCounters: @unchecked Sendable {
lock.unlock() lock.unlock()
} }
func firstTokenGenerated(requestId: String) {
let now = Date()
lock.lock()
guard var state = requestPhases[requestId], !state.hasRecordedFirstToken else {
lock.unlock()
return
}
state.hasRecordedFirstToken = true
requestPhases[requestId] = state
_timeToFirstToken = max(now.timeIntervalSince(state.requestStartedAt), 0)
lock.unlock()
}
func tokenGenerated(tokensPerSecond: Double, totalGenerated: Int) { func tokenGenerated(tokensPerSecond: Double, totalGenerated: Int) {
lock.lock() lock.lock()
_generationTokens = totalGenerated _generationTokens = totalGenerated
@@ -90,6 +145,55 @@ final class LiveCounters: @unchecked Sendable {
lock.unlock() lock.unlock()
} }
func recordPrefillReuse(requestId: String, matchedPromptTokens: Int, promptTokenCount: Int) {
lock.lock()
guard var state = requestPhases[requestId] else {
lock.unlock()
return
}
let matched = max(0, matchedPromptTokens)
let rebuilt = max(0, promptTokenCount - matched)
_totalCacheReusePromptTokens += matched
_totalCacheRebuildPromptTokens += rebuilt
_cacheMatchDepth = matched
state.matchedPromptTokens = matched
state.rebuiltPromptTokens = rebuilt
requestPhases[requestId] = state
refreshCurrentCachePromptStatsLocked()
lock.unlock()
}
func visionProcessingCompleted(requestId: String, duration: TimeInterval) {
let clampedDuration = max(duration, 0)
lock.lock()
guard var state = requestPhases[requestId] else {
lock.unlock()
return
}
_visionEncoderTime = clampedDuration
_totalVisionEncoderDuration += clampedDuration
state.visionEncoderTime = clampedDuration
requestPhases[requestId] = state
lock.unlock()
}
func disconnectDetected(requestId: String) {
lock.lock()
guard var state = requestPhases[requestId], !state.disconnectRecorded else {
lock.unlock()
return
}
state.disconnectRecorded = true
requestPhases[requestId] = state
_totalDisconnects += 1
lock.unlock()
}
func requestCompleted(requestId: String, generationTokens: Int) { func requestCompleted(requestId: String, generationTokens: Int) {
let now = Date() let now = Date()
lock.lock() lock.lock()
@@ -108,6 +212,7 @@ final class LiveCounters: @unchecked Sendable {
_isGenerating = _generatingRequests > 0 _isGenerating = _generatingRequests > 0
} }
refreshCurrentPhaseElapsed(now: now) refreshCurrentPhaseElapsed(now: now)
refreshCurrentCachePromptStatsLocked()
lock.unlock() lock.unlock()
} }
@@ -122,17 +227,27 @@ final class LiveCounters: @unchecked Sendable {
_promptTokens = 0 _promptTokens = 0
_generationTokens = 0 _generationTokens = 0
_tokensPerSecond = 0 _tokensPerSecond = 0
_prefillTokensPerSecond = 0
_timeToFirstToken = 0
_isPrefilling = false _isPrefilling = false
_isGenerating = false _isGenerating = false
_contextMax = 0 _contextMax = 0
_currentPhaseElapsed = 0 _currentPhaseElapsed = 0
_currentCacheMatchedPromptTokens = 0
_currentCacheRebuiltPromptTokens = 0
_cacheMatchDepth = 0
_visionEncoderTime = 0
_totalRequests = 0 _totalRequests = 0
_totalPromptTokens = 0 _totalPromptTokens = 0
_totalGenerationTokens = 0 _totalGenerationTokens = 0
_totalCacheReusePromptTokens = 0
_totalCacheRebuildPromptTokens = 0
_totalPreparingDuration = 0 _totalPreparingDuration = 0
_totalSessionBuildDuration = 0 _totalSessionBuildDuration = 0
_totalPrefillDuration = 0 _totalPrefillDuration = 0
_totalGenerationDuration = 0 _totalGenerationDuration = 0
_totalVisionEncoderDuration = 0
_totalDisconnects = 0
lock.unlock() lock.unlock()
} }
@@ -150,17 +265,27 @@ final class LiveCounters: @unchecked Sendable {
promptTokens: _promptTokens, promptTokens: _promptTokens,
generationTokens: _generationTokens, generationTokens: _generationTokens,
tokensPerSecond: _tokensPerSecond, tokensPerSecond: _tokensPerSecond,
prefillTokensPerSecond: _prefillTokensPerSecond,
timeToFirstToken: _timeToFirstToken,
isPrefilling: _isPrefilling, isPrefilling: _isPrefilling,
isGenerating: _isGenerating, isGenerating: _isGenerating,
contextMax: _contextMax, contextMax: _contextMax,
currentPhaseElapsed: _currentPhaseElapsed, currentPhaseElapsed: _currentPhaseElapsed,
currentCacheMatchedPromptTokens: _currentCacheMatchedPromptTokens,
currentCacheRebuiltPromptTokens: _currentCacheRebuiltPromptTokens,
cacheMatchDepth: _cacheMatchDepth,
visionEncoderTime: _visionEncoderTime,
totalRequests: _totalRequests, totalRequests: _totalRequests,
totalPromptTokens: _totalPromptTokens, totalPromptTokens: _totalPromptTokens,
totalGenerationTokens: _totalGenerationTokens, totalGenerationTokens: _totalGenerationTokens,
totalCacheReusePromptTokens: _totalCacheReusePromptTokens,
totalCacheRebuildPromptTokens: _totalCacheRebuildPromptTokens,
totalPreparingDuration: _totalPreparingDuration, totalPreparingDuration: _totalPreparingDuration,
totalSessionBuildDuration: _totalSessionBuildDuration, totalSessionBuildDuration: _totalSessionBuildDuration,
totalPrefillDuration: _totalPrefillDuration, totalPrefillDuration: _totalPrefillDuration,
totalGenerationDuration: _totalGenerationDuration totalGenerationDuration: _totalGenerationDuration,
totalVisionEncoderDuration: _totalVisionEncoderDuration,
totalDisconnects: _totalDisconnects
) )
lock.unlock() lock.unlock()
return s return s
@@ -175,17 +300,27 @@ final class LiveCounters: @unchecked Sendable {
let promptTokens: Int let promptTokens: Int
let generationTokens: Int let generationTokens: Int
let tokensPerSecond: Double let tokensPerSecond: Double
let prefillTokensPerSecond: Double
let timeToFirstToken: TimeInterval
let isPrefilling: Bool let isPrefilling: Bool
let isGenerating: Bool let isGenerating: Bool
let contextMax: Int let contextMax: Int
let currentPhaseElapsed: TimeInterval let currentPhaseElapsed: TimeInterval
let currentCacheMatchedPromptTokens: Int
let currentCacheRebuiltPromptTokens: Int
let cacheMatchDepth: Int
let visionEncoderTime: TimeInterval
let totalRequests: Int let totalRequests: Int
let totalPromptTokens: Int let totalPromptTokens: Int
let totalGenerationTokens: Int let totalGenerationTokens: Int
let totalCacheReusePromptTokens: Int
let totalCacheRebuildPromptTokens: Int
let totalPreparingDuration: TimeInterval let totalPreparingDuration: TimeInterval
let totalSessionBuildDuration: TimeInterval let totalSessionBuildDuration: TimeInterval
let totalPrefillDuration: TimeInterval let totalPrefillDuration: TimeInterval
let totalGenerationDuration: TimeInterval let totalGenerationDuration: TimeInterval
let totalVisionEncoderDuration: TimeInterval
let totalDisconnects: Int
} }
private func incrementCount(for phase: RequestPhase) { private func incrementCount(for phase: RequestPhase) {
@@ -231,9 +366,20 @@ final class LiveCounters: @unchecked Sendable {
_currentPhaseElapsed = requestPhases.values.map { now.timeIntervalSince($0.phaseStartedAt) }.max() ?? 0 _currentPhaseElapsed = requestPhases.values.map { now.timeIntervalSince($0.phaseStartedAt) }.max() ?? 0
} }
private func refreshCurrentCachePromptStatsLocked() {
_currentCacheMatchedPromptTokens = requestPhases.values.reduce(0) { $0 + $1.matchedPromptTokens }
_currentCacheRebuiltPromptTokens = requestPhases.values.reduce(0) { $0 + $1.rebuiltPromptTokens }
}
private struct RequestState { private struct RequestState {
var phase: RequestPhase var phase: RequestPhase
var phaseStartedAt: Date var phaseStartedAt: Date
var requestStartedAt: Date
var matchedPromptTokens: Int = 0
var rebuiltPromptTokens: Int = 0
var hasRecordedFirstToken: Bool = false
var disconnectRecorded: Bool = false
var visionEncoderTime: TimeInterval = 0
} }
enum RequestPhase { enum RequestPhase {
@@ -261,34 +407,50 @@ final class InferenceStats {
var isGenerating: Bool = false var isGenerating: Bool = false
var isPrefilling: Bool = false var isPrefilling: Bool = false
var currentTokensPerSecond: Double = 0 var currentTokensPerSecond: Double = 0
var prefillTokensPerSecond: Double = 0
var timeToFirstToken: TimeInterval = 0
var contextUsed: Int = 0 var contextUsed: Int = 0
var contextMax: Int = 0 var contextMax: Int = 0
var currentPhaseElapsed: TimeInterval = 0 var currentPhaseElapsed: TimeInterval = 0
var currentCacheMatchedPromptTokens: Int = 0
var currentCacheRebuiltPromptTokens: Int = 0
var cacheMatchDepth: Int = 0
var visionEncoderTime: TimeInterval = 0
// MARK: - Cumulative counters // MARK: - Cumulative counters
var totalRequests: Int = 0 var totalRequests: Int = 0
var totalPromptTokens: Int = 0 var totalPromptTokens: Int = 0
var totalGenerationTokens: Int = 0 var totalGenerationTokens: Int = 0
var totalCacheReusePromptTokens: Int = 0
var totalCacheRebuildPromptTokens: Int = 0
var totalCacheHits: Int = 0 var totalCacheHits: Int = 0
var totalCacheMisses: Int = 0 var totalCacheMisses: Int = 0
var totalCacheEvictions: Int = 0 var totalCacheEvictions: Int = 0
var totalCacheReusePromptTokens: Int = 0 var cacheHitRatePercent: Double = 0
var totalCacheRebuildPromptTokens: Int = 0 var totalPrefixHits: Int = 0
var totalSupersequenceHits: Int = 0
var totalLCPHits: Int = 0
var totalPreparingDuration: TimeInterval = 0 var totalPreparingDuration: TimeInterval = 0
var totalSessionBuildDuration: TimeInterval = 0 var totalSessionBuildDuration: TimeInterval = 0
var totalPrefillDuration: TimeInterval = 0 var totalPrefillDuration: TimeInterval = 0
var totalGenerationDuration: TimeInterval = 0 var totalGenerationDuration: TimeInterval = 0
var totalVisionEncoderDuration: TimeInterval = 0
var totalDisconnects: Int = 0
// MARK: - Cache state // MARK: - Cache state
var cacheEntryCount: Int = 0 var cacheEntryCount: Int = 0
var warmCacheEntryCount: Int = 0
var activeCacheEntryCount: Int = 0
var generatingCacheEntryCount: Int = 0
var cacheEstimatedBytes: Int = 0 var cacheEstimatedBytes: Int = 0
var cacheEstimatedTokens: Int = 0 var cacheEstimatedTokens: Int = 0
var cachedSessions: [ConversationSessionCache.SessionSummary] = [] var cacheMemoryBudgetBytes: Int = 0
var cacheMemoryUsagePercent: Double = 0
var cachedEntries: [TokenPrefixCache.EntrySummary] = []
// MARK: - Quantization stats (Phase 6)
var kvQuantizationEnabled: Bool = false
var quantizationBytesSaved: Int = 0
// MARK: - Time series data (ring buffers for charts) // MARK: - Time series data (ring buffers for charts)
@@ -302,13 +464,18 @@ final class InferenceStats {
private(set) var promptTokenHistory: [DataPoint] = [] private(set) var promptTokenHistory: [DataPoint] = []
private(set) var generationTokenHistory: [DataPoint] = [] private(set) var generationTokenHistory: [DataPoint] = []
private(set) var cacheEntryHistory: [DataPoint] = [] private(set) var cacheEntryHistory: [DataPoint] = []
private(set) var activeSessionHistory: [DataPoint] = []
private(set) var cacheFootprintHistory: [DataPoint] = [] private(set) var cacheFootprintHistory: [DataPoint] = []
private(set) var cacheReuseHistory: [DataPoint] = [] private(set) var cacheHitRateHistory: [DataPoint] = []
private(set) var cacheRebuildHistory: [DataPoint] = [] private(set) var cacheMemoryPressureHistory: [DataPoint] = []
private(set) var currentPhaseElapsedHistory: [DataPoint] = [] private(set) var currentPhaseElapsedHistory: [DataPoint] = []
private(set) var prefillDurationHistory: [DataPoint] = [] private(set) var prefillDurationHistory: [DataPoint] = []
private(set) var sessionBuildDurationHistory: [DataPoint] = [] private(set) var cacheReusePromptHistory: [DataPoint] = []
private(set) var cacheRebuildPromptHistory: [DataPoint] = []
private(set) var cacheMatchQualityHistory: [DataPoint] = []
private(set) var ttftHistory: [DataPoint] = []
private(set) var prefillSpeedHistory: [DataPoint] = []
private(set) var cacheMatchDepthHistory: [DataPoint] = []
private(set) var visionTimeHistory: [DataPoint] = []
private static let maxHistoryPoints = 120 // ~2 minutes at 1Hz private static let maxHistoryPoints = 120 // ~2 minutes at 1Hz
@@ -316,10 +483,9 @@ final class InferenceStats {
private var sampleTimer: Timer? private var sampleTimer: Timer?
private var lastGenerationTokenCount: Int = 0 private var lastGenerationTokenCount: Int = 0
private var lastPromptTokenCount: Int = 0 private var lastPromptTokenCount: Int = 0
private var lastCacheReuseTokenCount: Int = 0
private var lastCacheRebuildTokenCount: Int = 0
private var lastPrefillDuration: TimeInterval = 0 private var lastPrefillDuration: TimeInterval = 0
private var lastSessionBuildDuration: TimeInterval = 0 private var lastCacheReusePromptTokenCount: Int = 0
private var lastCacheRebuildPromptTokenCount: Int = 0
func startSampling() { func startSampling() {
guard sampleTimer == nil else { return } guard sampleTimer == nil else { return }
@@ -338,7 +504,7 @@ final class InferenceStats {
private func recordSample() { private func recordSample() {
// Pull live values from the thread-safe counters // Pull live values from the thread-safe counters
let snap = LiveCounters.shared.snapshot() let snap = LiveCounters.shared.snapshot()
let cache = ConversationSessionCache.shared.snapshot() let cache = TokenPrefixCache.shared.snapshot()
activeRequests = snap.activeRequests activeRequests = snap.activeRequests
preparingRequests = snap.preparingRequests preparingRequests = snap.preparingRequests
@@ -348,56 +514,75 @@ final class InferenceStats {
currentPromptTokens = snap.promptTokens currentPromptTokens = snap.promptTokens
currentGenerationTokens = snap.generationTokens currentGenerationTokens = snap.generationTokens
currentTokensPerSecond = snap.tokensPerSecond currentTokensPerSecond = snap.tokensPerSecond
prefillTokensPerSecond = snap.prefillTokensPerSecond
timeToFirstToken = snap.timeToFirstToken
isPrefilling = snap.isPrefilling isPrefilling = snap.isPrefilling
isGenerating = snap.isGenerating isGenerating = snap.isGenerating
contextMax = snap.contextMax contextMax = snap.contextMax
contextUsed = snap.promptTokens + snap.generationTokens contextUsed = snap.promptTokens + snap.generationTokens
currentPhaseElapsed = snap.currentPhaseElapsed currentPhaseElapsed = snap.currentPhaseElapsed
currentCacheMatchedPromptTokens = snap.currentCacheMatchedPromptTokens
currentCacheRebuiltPromptTokens = snap.currentCacheRebuiltPromptTokens
cacheMatchDepth = snap.cacheMatchDepth
visionEncoderTime = snap.visionEncoderTime
totalRequests = snap.totalRequests totalRequests = snap.totalRequests
totalPromptTokens = snap.totalPromptTokens totalPromptTokens = snap.totalPromptTokens
totalGenerationTokens = snap.totalGenerationTokens totalGenerationTokens = snap.totalGenerationTokens
totalCacheReusePromptTokens = snap.totalCacheReusePromptTokens
totalCacheRebuildPromptTokens = snap.totalCacheRebuildPromptTokens
totalPreparingDuration = snap.totalPreparingDuration totalPreparingDuration = snap.totalPreparingDuration
totalSessionBuildDuration = snap.totalSessionBuildDuration totalSessionBuildDuration = snap.totalSessionBuildDuration
totalPrefillDuration = snap.totalPrefillDuration totalPrefillDuration = snap.totalPrefillDuration
totalGenerationDuration = snap.totalGenerationDuration totalGenerationDuration = snap.totalGenerationDuration
totalVisionEncoderDuration = snap.totalVisionEncoderDuration
totalDisconnects = snap.totalDisconnects
totalCacheHits = cache.totalHits totalCacheHits = cache.totalHits
totalCacheMisses = cache.totalMisses totalCacheMisses = cache.totalMisses
totalCacheEvictions = cache.totalEvictions totalCacheEvictions = cache.totalEvictions
totalCacheReusePromptTokens = cache.totalReusePromptTokens cacheHitRatePercent = cache.hitRate
totalCacheRebuildPromptTokens = cache.totalRebuildPromptTokens totalPrefixHits = cache.prefixHits
totalSupersequenceHits = cache.supersequenceHits
totalLCPHits = cache.lcpHits
cacheEntryCount = cache.totalEntries cacheEntryCount = cache.totalEntries
warmCacheEntryCount = cache.warmEntries
activeCacheEntryCount = cache.activeEntries
generatingCacheEntryCount = cache.generatingEntries
cacheEstimatedBytes = cache.estimatedBytes cacheEstimatedBytes = cache.estimatedBytes
cacheEstimatedTokens = cache.cachedTokenEstimate cacheEstimatedTokens = cache.totalCachedTokens
cachedSessions = cache.sessions cacheMemoryBudgetBytes = cache.memoryBudgetBytes
cacheMemoryUsagePercent = cache.memoryUsagePercent
cachedEntries = cache.entries
kvQuantizationEnabled = cache.quantizationEnabled
quantizationBytesSaved = cache.quantizationBytesSaved
let now = Date.now let now = Date.now
let genDelta = snap.totalGenerationTokens - lastGenerationTokenCount let genDelta = snap.totalGenerationTokens - lastGenerationTokenCount
let promptDelta = snap.totalPromptTokens - lastPromptTokenCount let promptDelta = snap.totalPromptTokens - lastPromptTokenCount
let cacheReuseDelta = cache.totalReusePromptTokens - lastCacheReuseTokenCount
let cacheRebuildDelta = cache.totalRebuildPromptTokens - lastCacheRebuildTokenCount
let prefillDurationDelta = snap.totalPrefillDuration - lastPrefillDuration let prefillDurationDelta = snap.totalPrefillDuration - lastPrefillDuration
let sessionBuildDurationDelta = snap.totalSessionBuildDuration - lastSessionBuildDuration let cacheReusePromptDelta = snap.totalCacheReusePromptTokens - lastCacheReusePromptTokenCount
let cacheRebuildPromptDelta = snap.totalCacheRebuildPromptTokens - lastCacheRebuildPromptTokenCount
let cacheMatchQualityDelta = cacheReusePromptDelta + cacheRebuildPromptDelta > 0
? (Double(cacheReusePromptDelta) / Double(cacheReusePromptDelta + cacheRebuildPromptDelta)) * 100
: 0
lastGenerationTokenCount = snap.totalGenerationTokens lastGenerationTokenCount = snap.totalGenerationTokens
lastPromptTokenCount = snap.totalPromptTokens lastPromptTokenCount = snap.totalPromptTokens
lastCacheReuseTokenCount = cache.totalReusePromptTokens
lastCacheRebuildTokenCount = cache.totalRebuildPromptTokens
lastPrefillDuration = snap.totalPrefillDuration lastPrefillDuration = snap.totalPrefillDuration
lastSessionBuildDuration = snap.totalSessionBuildDuration lastCacheReusePromptTokenCount = snap.totalCacheReusePromptTokens
lastCacheRebuildPromptTokenCount = snap.totalCacheRebuildPromptTokens
tokenRateHistory.append(DataPoint(timestamp: now, value: snap.tokensPerSecond)) tokenRateHistory.append(DataPoint(timestamp: now, value: snap.tokensPerSecond))
generationTokenHistory.append(DataPoint(timestamp: now, value: Double(genDelta))) generationTokenHistory.append(DataPoint(timestamp: now, value: Double(genDelta)))
promptTokenHistory.append(DataPoint(timestamp: now, value: Double(promptDelta))) promptTokenHistory.append(DataPoint(timestamp: now, value: Double(promptDelta)))
cacheEntryHistory.append(DataPoint(timestamp: now, value: Double(cache.totalEntries))) cacheEntryHistory.append(DataPoint(timestamp: now, value: Double(cache.totalEntries)))
activeSessionHistory.append(DataPoint(timestamp: now, value: Double(cache.activeEntries)))
cacheFootprintHistory.append(DataPoint(timestamp: now, value: Double(cache.estimatedBytes))) cacheFootprintHistory.append(DataPoint(timestamp: now, value: Double(cache.estimatedBytes)))
cacheReuseHistory.append(DataPoint(timestamp: now, value: Double(cacheReuseDelta))) cacheHitRateHistory.append(DataPoint(timestamp: now, value: cache.hitRate))
cacheRebuildHistory.append(DataPoint(timestamp: now, value: Double(cacheRebuildDelta))) cacheMemoryPressureHistory.append(DataPoint(timestamp: now, value: cache.memoryUsagePercent))
currentPhaseElapsedHistory.append(DataPoint(timestamp: now, value: snap.currentPhaseElapsed)) currentPhaseElapsedHistory.append(DataPoint(timestamp: now, value: snap.currentPhaseElapsed))
prefillDurationHistory.append(DataPoint(timestamp: now, value: prefillDurationDelta)) prefillDurationHistory.append(DataPoint(timestamp: now, value: prefillDurationDelta))
sessionBuildDurationHistory.append(DataPoint(timestamp: now, value: sessionBuildDurationDelta)) cacheReusePromptHistory.append(DataPoint(timestamp: now, value: Double(cacheReusePromptDelta)))
cacheRebuildPromptHistory.append(DataPoint(timestamp: now, value: Double(cacheRebuildPromptDelta)))
cacheMatchQualityHistory.append(DataPoint(timestamp: now, value: cacheMatchQualityDelta))
ttftHistory.append(DataPoint(timestamp: now, value: snap.timeToFirstToken * 1_000))
prefillSpeedHistory.append(DataPoint(timestamp: now, value: snap.prefillTokensPerSecond))
cacheMatchDepthHistory.append(DataPoint(timestamp: now, value: Double(snap.cacheMatchDepth)))
visionTimeHistory.append(DataPoint(timestamp: now, value: snap.visionEncoderTime * 1_000))
if tokenRateHistory.count > Self.maxHistoryPoints { if tokenRateHistory.count > Self.maxHistoryPoints {
tokenRateHistory.removeFirst(tokenRateHistory.count - Self.maxHistoryPoints) tokenRateHistory.removeFirst(tokenRateHistory.count - Self.maxHistoryPoints)
@@ -411,17 +596,14 @@ final class InferenceStats {
if cacheEntryHistory.count > Self.maxHistoryPoints { if cacheEntryHistory.count > Self.maxHistoryPoints {
cacheEntryHistory.removeFirst(cacheEntryHistory.count - Self.maxHistoryPoints) cacheEntryHistory.removeFirst(cacheEntryHistory.count - Self.maxHistoryPoints)
} }
if activeSessionHistory.count > Self.maxHistoryPoints {
activeSessionHistory.removeFirst(activeSessionHistory.count - Self.maxHistoryPoints)
}
if cacheFootprintHistory.count > Self.maxHistoryPoints { if cacheFootprintHistory.count > Self.maxHistoryPoints {
cacheFootprintHistory.removeFirst(cacheFootprintHistory.count - Self.maxHistoryPoints) cacheFootprintHistory.removeFirst(cacheFootprintHistory.count - Self.maxHistoryPoints)
} }
if cacheReuseHistory.count > Self.maxHistoryPoints { if cacheHitRateHistory.count > Self.maxHistoryPoints {
cacheReuseHistory.removeFirst(cacheReuseHistory.count - Self.maxHistoryPoints) cacheHitRateHistory.removeFirst(cacheHitRateHistory.count - Self.maxHistoryPoints)
} }
if cacheRebuildHistory.count > Self.maxHistoryPoints { if cacheMemoryPressureHistory.count > Self.maxHistoryPoints {
cacheRebuildHistory.removeFirst(cacheRebuildHistory.count - Self.maxHistoryPoints) cacheMemoryPressureHistory.removeFirst(cacheMemoryPressureHistory.count - Self.maxHistoryPoints)
} }
if currentPhaseElapsedHistory.count > Self.maxHistoryPoints { if currentPhaseElapsedHistory.count > Self.maxHistoryPoints {
currentPhaseElapsedHistory.removeFirst(currentPhaseElapsedHistory.count - Self.maxHistoryPoints) currentPhaseElapsedHistory.removeFirst(currentPhaseElapsedHistory.count - Self.maxHistoryPoints)
@@ -429,14 +611,32 @@ final class InferenceStats {
if prefillDurationHistory.count > Self.maxHistoryPoints { if prefillDurationHistory.count > Self.maxHistoryPoints {
prefillDurationHistory.removeFirst(prefillDurationHistory.count - Self.maxHistoryPoints) prefillDurationHistory.removeFirst(prefillDurationHistory.count - Self.maxHistoryPoints)
} }
if sessionBuildDurationHistory.count > Self.maxHistoryPoints { if cacheReusePromptHistory.count > Self.maxHistoryPoints {
sessionBuildDurationHistory.removeFirst(sessionBuildDurationHistory.count - Self.maxHistoryPoints) cacheReusePromptHistory.removeFirst(cacheReusePromptHistory.count - Self.maxHistoryPoints)
}
if cacheRebuildPromptHistory.count > Self.maxHistoryPoints {
cacheRebuildPromptHistory.removeFirst(cacheRebuildPromptHistory.count - Self.maxHistoryPoints)
}
if cacheMatchQualityHistory.count > Self.maxHistoryPoints {
cacheMatchQualityHistory.removeFirst(cacheMatchQualityHistory.count - Self.maxHistoryPoints)
}
if ttftHistory.count > Self.maxHistoryPoints {
ttftHistory.removeFirst(ttftHistory.count - Self.maxHistoryPoints)
}
if prefillSpeedHistory.count > Self.maxHistoryPoints {
prefillSpeedHistory.removeFirst(prefillSpeedHistory.count - Self.maxHistoryPoints)
}
if cacheMatchDepthHistory.count > Self.maxHistoryPoints {
cacheMatchDepthHistory.removeFirst(cacheMatchDepthHistory.count - Self.maxHistoryPoints)
}
if visionTimeHistory.count > Self.maxHistoryPoints {
visionTimeHistory.removeFirst(visionTimeHistory.count - Self.maxHistoryPoints)
} }
} }
func reset() { func reset() {
LiveCounters.shared.reset() LiveCounters.shared.reset()
ConversationSessionCache.shared.reset() TokenPrefixCache.shared.reset()
activeRequests = 0 activeRequests = 0
preparingRequests = 0 preparingRequests = 0
sessionBuildRequests = 0 sessionBuildRequests = 0
@@ -447,44 +647,71 @@ final class InferenceStats {
isGenerating = false isGenerating = false
isPrefilling = false isPrefilling = false
currentTokensPerSecond = 0 currentTokensPerSecond = 0
prefillTokensPerSecond = 0
timeToFirstToken = 0
contextUsed = 0 contextUsed = 0
contextMax = 0 contextMax = 0
currentPhaseElapsed = 0 currentPhaseElapsed = 0
currentCacheMatchedPromptTokens = 0
currentCacheRebuiltPromptTokens = 0
cacheMatchDepth = 0
visionEncoderTime = 0
totalRequests = 0 totalRequests = 0
totalPromptTokens = 0 totalPromptTokens = 0
totalGenerationTokens = 0 totalGenerationTokens = 0
totalCacheReusePromptTokens = 0
totalCacheRebuildPromptTokens = 0
totalPreparingDuration = 0 totalPreparingDuration = 0
totalSessionBuildDuration = 0 totalSessionBuildDuration = 0
totalPrefillDuration = 0 totalPrefillDuration = 0
totalGenerationDuration = 0 totalGenerationDuration = 0
totalVisionEncoderDuration = 0
totalDisconnects = 0
totalCacheHits = 0 totalCacheHits = 0
totalCacheMisses = 0 totalCacheMisses = 0
totalCacheEvictions = 0 totalCacheEvictions = 0
totalCacheReusePromptTokens = 0 cacheHitRatePercent = 0
totalCacheRebuildPromptTokens = 0 totalPrefixHits = 0
totalSupersequenceHits = 0
totalLCPHits = 0
cacheEntryCount = 0 cacheEntryCount = 0
warmCacheEntryCount = 0
activeCacheEntryCount = 0
generatingCacheEntryCount = 0
cacheEstimatedBytes = 0 cacheEstimatedBytes = 0
cacheEstimatedTokens = 0 cacheEstimatedTokens = 0
cachedSessions.removeAll() cacheMemoryBudgetBytes = 0
cacheMemoryUsagePercent = 0
cachedEntries.removeAll()
tokenRateHistory.removeAll() tokenRateHistory.removeAll()
promptTokenHistory.removeAll() promptTokenHistory.removeAll()
generationTokenHistory.removeAll() generationTokenHistory.removeAll()
cacheEntryHistory.removeAll() cacheEntryHistory.removeAll()
activeSessionHistory.removeAll()
cacheFootprintHistory.removeAll() cacheFootprintHistory.removeAll()
cacheReuseHistory.removeAll() cacheHitRateHistory.removeAll()
cacheRebuildHistory.removeAll() cacheMemoryPressureHistory.removeAll()
currentPhaseElapsedHistory.removeAll() currentPhaseElapsedHistory.removeAll()
prefillDurationHistory.removeAll() prefillDurationHistory.removeAll()
sessionBuildDurationHistory.removeAll() cacheReusePromptHistory.removeAll()
cacheRebuildPromptHistory.removeAll()
cacheMatchQualityHistory.removeAll()
ttftHistory.removeAll()
prefillSpeedHistory.removeAll()
cacheMatchDepthHistory.removeAll()
visionTimeHistory.removeAll()
lastGenerationTokenCount = 0 lastGenerationTokenCount = 0
lastPromptTokenCount = 0 lastPromptTokenCount = 0
lastCacheReuseTokenCount = 0
lastCacheRebuildTokenCount = 0
lastPrefillDuration = 0 lastPrefillDuration = 0
lastSessionBuildDuration = 0 lastCacheReusePromptTokenCount = 0
lastCacheRebuildPromptTokenCount = 0
}
var currentCacheMatchQualityPercent: Double {
let total = currentCacheMatchedPromptTokens + currentCacheRebuiltPromptTokens
guard total > 0 else { return 0 }
return (Double(currentCacheMatchedPromptTokens) / Double(total)) * 100
}
var totalCacheMatchQualityPercent: Double {
let total = totalCacheReusePromptTokens + totalCacheRebuildPromptTokens
guard total > 0 else { return 0 }
return (Double(totalCacheReusePromptTokens) / Double(total)) * 100
} }
} }

36
MLXServer/Models/ModelConfig.swift
View File

@@ -15,6 +15,7 @@ struct ModelConfig: Identifiable, Hashable {
let loaderKind: LoaderKind let loaderKind: LoaderKind
let supportsImages: Bool let supportsImages: Bool
let supportsTools: Bool let supportsTools: Bool
let defaultGenerationSettings: GenerationSettings
/// All models supported by the app. /// All models supported by the app.
static let availableModels: [ModelConfig] = [ static let availableModels: [ModelConfig] = [
@@ -25,16 +26,28 @@ struct ModelConfig: Identifiable, Hashable {
contextLength: 128_000, contextLength: 128_000,
loaderKind: .vlm, loaderKind: .vlm,
supportsImages: true, supportsImages: true,
supportsTools: true supportsTools: true,
defaultGenerationSettings: .technicalDefault
), ),
ModelConfig( ModelConfig(
id: "qwen", id: "qwen",
repoId: "mlx-community/Qwen3-VL-4B-Instruct-4bit", repoId: "mlx-community/Qwen3.5-4B-MLX-4bit",
displayName: "Qwen3 VL 4B", displayName: "Qwen3.5 4B",
contextLength: 256_000, contextLength: 256_000,
loaderKind: .vlm, loaderKind: .vlm,
supportsImages: true, supportsImages: true,
supportsTools: true supportsTools: true,
defaultGenerationSettings: .technicalDefault
),
ModelConfig(
id: "qwen3.5-0.8b",
repoId: "mlx-community/Qwen3.5-0.8B-4bit",
displayName: "Qwen3.5 0.8B",
contextLength: 256_000,
loaderKind: .vlm,
supportsImages: true,
supportsTools: true,
defaultGenerationSettings: .technicalDefault
), ),
ModelConfig( ModelConfig(
id: "qwen3.5-9b", id: "qwen3.5-9b",
@@ -43,7 +56,8 @@ struct ModelConfig: Identifiable, Hashable {
contextLength: 256_000, contextLength: 256_000,
loaderKind: .vlm, loaderKind: .vlm,
supportsImages: true, supportsImages: true,
supportsTools: true supportsTools: true,
defaultGenerationSettings: .technicalDefault
), ),
ModelConfig( ModelConfig(
id: "stheno", id: "stheno",
@@ -52,16 +66,8 @@ struct ModelConfig: Identifiable, Hashable {
contextLength: 8_192, contextLength: 8_192,
loaderKind: .llm, loaderKind: .llm,
supportsImages: false, supportsImages: false,
supportsTools: false supportsTools: false,
), defaultGenerationSettings: .roleplayDefault
ModelConfig(
id: "unslopnemo",
repoId: "mlx-community/UnslopNemo-12B-v4.1-4bit",
displayName: "UnslopNemo 12B",
contextLength: 131_072,
loaderKind: .llm,
supportsImages: false,
supportsTools: false
), ),
] ]

37
MLXServer/Server/APIModels.swift
View File

@@ -152,15 +152,52 @@ struct APIChatCompletionRequest: Codable {
let messages: [APIChatMessage] let messages: [APIChatMessage]
let temperature: Double? let temperature: Double?
let top_p: Double? let top_p: Double?
let top_k: Int?
let min_p: Double?
let max_tokens: Int? let max_tokens: Int?
let stream: Bool? let stream: Bool?
let stop: StopSequence? let stop: StopSequence?
let tools: [APIToolDefinition]? let tools: [APIToolDefinition]?
let tool_choice: AnyCodable? let tool_choice: AnyCodable?
let repetition_penalty: Double?
let frequency_penalty: Double? let frequency_penalty: Double?
let presence_penalty: Double? let presence_penalty: Double?
let n: Int? let n: Int?
init(
model: String?,
messages: [APIChatMessage],
temperature: Double? = nil,
top_p: Double? = nil,
max_tokens: Int? = nil,
stream: Bool? = nil,
stop: StopSequence? = nil,
tools: [APIToolDefinition]? = nil,
tool_choice: AnyCodable? = nil,
frequency_penalty: Double? = nil,
presence_penalty: Double? = nil,
n: Int? = nil,
top_k: Int? = nil,
min_p: Double? = nil,
repetition_penalty: Double? = nil
) {
self.model = model
self.messages = messages
self.temperature = temperature
self.top_p = top_p
self.top_k = top_k
self.min_p = min_p
self.max_tokens = max_tokens
self.stream = stream
self.stop = stop
self.tools = tools
self.tool_choice = tool_choice
self.repetition_penalty = repetition_penalty
self.frequency_penalty = frequency_penalty
self.presence_penalty = presence_penalty
self.n = n
}
enum StopSequence: Codable { enum StopSequence: Codable {
case single(String) case single(String)
case multiple([String]) case multiple([String])

687
MLXServer/Server/APIServer.swift
View File

@@ -1,4 +1,3 @@
import AppKit
import Foundation import Foundation
import MLXLMCommon import MLXLMCommon
import Network import Network
@@ -8,6 +7,28 @@ import Network
@Observable @Observable
@MainActor @MainActor
final class APIServer { final class APIServer {
struct DebugLookupEvent: Sendable {
let requestId: String
let modelId: String
let promptTokenCount: Int
let isHit: Bool
let matchedTokenCount: Int
}
struct DebugGenerationSettingsEvent: Sendable {
let requestId: String
let modelId: String
let settings: GenerationSettings
}
private struct ActiveRequest {
let connection: NWConnection
let cancellation: CancellationToken
}
nonisolated(unsafe) static var debugLookupEventHandler: (@Sendable (DebugLookupEvent) -> Void)?
nonisolated(unsafe) static var debugGenerationSettingsEventHandler: (@Sendable (DebugGenerationSettingsEvent) -> Void)?
var isRunning = false var isRunning = false
var port: Int = 1234 var port: Int = 1234
var requestCount: Int = 0 var requestCount: Int = 0
@@ -15,11 +36,14 @@ final class APIServer {
private var listener: NWListener? private var listener: NWListener?
private var modelManager: ModelManager? private var modelManager: ModelManager?
private var activeRequests: [String: ActiveRequest] = [:]
private var isShuttingDown = false
func start(modelManager: ModelManager, port: Int = 1234) { func start(modelManager: ModelManager, port: Int = 1234) {
guard !isRunning else { return } guard !isRunning else { return }
self.modelManager = modelManager self.modelManager = modelManager
self.port = port self.port = port
self.isShuttingDown = false
do { do {
let params = NWParameters.tcp let params = NWParameters.tcp
@@ -61,11 +85,46 @@ final class APIServer {
} }
func stop() { func stop() {
beginShutdown()
TokenPrefixCache.shared.invalidateAll()
inferenceStats.stopSampling()
}
func shutdown(timeoutSeconds: TimeInterval = 2.0) async {
beginShutdown()
let deadline = Date().addingTimeInterval(timeoutSeconds)
while !activeRequests.isEmpty && Date() < deadline {
try? await Task.sleep(nanoseconds: 10_000_000)
}
TokenPrefixCache.shared.invalidateAll()
inferenceStats.stopSampling()
}
private func beginShutdown() {
guard !isShuttingDown else { return }
isShuttingDown = true
listener?.cancel() listener?.cancel()
listener = nil listener = nil
isRunning = false isRunning = false
ConversationSessionCache.shared.invalidateAll()
inferenceStats.stopSampling() for activeRequest in activeRequests.values {
activeRequest.cancellation.cancel()
activeRequest.connection.cancel()
}
}
private func registerActiveRequest(
requestId: String,
connection: NWConnection,
cancellation: CancellationToken
) {
activeRequests[requestId] = ActiveRequest(connection: connection, cancellation: cancellation)
}
private func unregisterActiveRequest(requestId: String) {
activeRequests.removeValue(forKey: requestId)
} }
// MARK: - Connection handling // MARK: - Connection handling
@@ -162,6 +221,11 @@ final class APIServer {
// MARK: - POST /v1/chat/completions // MARK: - POST /v1/chat/completions
private func handleChatCompletions(connection: NWConnection, body: Data?) async { private func handleChatCompletions(connection: NWConnection, body: Data?) async {
guard !isShuttingDown else {
sendResponse(connection: connection, status: 503, body: #"{"error":"Server is shutting down"}"#)
return
}
guard let body, let request = try? JSONDecoder().decode(APIChatCompletionRequest.self, from: body) else { guard let body, let request = try? JSONDecoder().decode(APIChatCompletionRequest.self, from: body) else {
sendResponse(connection: connection, status: 400, body: #"{"error":"Invalid request body"}"#) sendResponse(connection: connection, status: 400, body: #"{"error":"Invalid request body"}"#)
return return
@@ -177,7 +241,7 @@ final class APIServer {
if let targetConfig = ModelConfig.resolve(requestedModel) { if let targetConfig = ModelConfig.resolve(requestedModel) {
if modelManager.currentModel?.id != targetConfig.id { if modelManager.currentModel?.id != targetConfig.id {
print("[APIServer] Swapping model: \(modelManager.currentModel?.repoId ?? "none") -> \(targetConfig.repoId)") print("[APIServer] Swapping model: \(modelManager.currentModel?.repoId ?? "none") -> \(targetConfig.repoId)")
ConversationSessionCache.shared.invalidateAll() TokenPrefixCache.shared.invalidateAll()
await modelManager.loadModel(targetConfig) await modelManager.loadModel(targetConfig)
} }
} }
@@ -188,7 +252,7 @@ final class APIServer {
if modelManager.modelContainer == nil, let lastModelId = Preferences.lastModelId, if modelManager.modelContainer == nil, let lastModelId = Preferences.lastModelId,
let config = ModelConfig.resolve(lastModelId) { let config = ModelConfig.resolve(lastModelId) {
print("[APIServer] Reloading idle-unloaded model: \(config.repoId)") print("[APIServer] Reloading idle-unloaded model: \(config.repoId)")
ConversationSessionCache.shared.invalidateAll() TokenPrefixCache.shared.invalidateAll()
await modelManager.loadModel(config) await modelManager.loadModel(config)
} }
@@ -199,15 +263,26 @@ final class APIServer {
modelManager.touchActivity() modelManager.touchActivity()
let isStream = request.stream ?? false
let temperature = request.temperature ?? 0.7
let topP = request.top_p ?? 1.0
let maxTokens = request.max_tokens ?? 4096
let requestId = "chatcmpl-\(UUID().uuidString.prefix(12).lowercased())" let requestId = "chatcmpl-\(UUID().uuidString.prefix(12).lowercased())"
let created = Int(Date().timeIntervalSince1970) let created = Int(Date().timeIntervalSince1970)
let modelName = request.model ?? modelManager.currentModel?.repoId ?? "unknown" let modelName = request.model ?? modelManager.currentModel?.repoId ?? "unknown"
let currentModel = modelManager.currentModel let currentModel = modelManager.currentModel
let contextLength = modelManager.currentModel?.contextLength ?? 0 let contextLength = modelManager.currentModel?.contextLength ?? 0
let baseSettings = Preferences.generationSettings(forModelId: currentModel?.id ?? ModelConfig.default.id)
let generationSettings = baseSettings.applying(
GenerationSettingsOverride(
temperature: request.temperature,
topP: request.top_p,
topK: request.top_k,
minP: request.min_p,
maxTokens: request.max_tokens,
repetitionPenalty: request.repetition_penalty,
presencePenalty: request.presence_penalty,
frequencyPenalty: request.frequency_penalty
)
)
let isStream = request.stream ?? false
let maxTokens = generationSettings.maxTokens
if let tools = request.tools, !tools.isEmpty, currentModel?.supportsTools != true { if let tools = request.tools, !tools.isEmpty, currentModel?.supportsTools != true {
sendResponse( sendResponse(
@@ -219,91 +294,20 @@ final class APIServer {
} }
LiveCounters.shared.requestStarted(requestId: requestId, contextLength: contextLength) LiveCounters.shared.requestStarted(requestId: requestId, contextLength: contextLength)
// Convert API messages to Chat.Message, extracting images from content parts
var chatMessages: [Chat.Message] = []
var messageSignatures: [UInt64] = []
var images: [UserInput.Image] = []
var estimatedBytes = 0
let currentModelRepoId = currentModel?.repoId ?? modelName let currentModelRepoId = currentModel?.repoId ?? modelName
// Build the instructions string (system prompt + tool definitions). let preparedPrompt = PromptBuilder.build(
// This is passed to ChatSession via `instructions:` rather than injected from: request,
// as history messages, so it avoids an expensive history-replay prefill. modelId: currentModelRepoId,
var instructions: String = "" thinkingEnabled: generationSettings.thinkingEnabled
)
// Collect system message text from the request
for msg in request.messages where msg.role == "system" {
let text = msg.content?.textContent ?? ""
if !text.isEmpty {
if !instructions.isEmpty { instructions += "\n\n" }
instructions += text
}
}
// Append tool definitions to instructions
if let tools = request.tools, !tools.isEmpty {
let toolSystemPrompt = ToolPromptBuilder.buildSystemPrompt(tools: tools, modelId: currentModelRepoId)
if !instructions.isEmpty { instructions += "\n\n" }
instructions += toolSystemPrompt
}
let isQwen = currentModelRepoId.lowercased().contains("qwen") let isQwen = currentModelRepoId.lowercased().contains("qwen")
estimatedBytes += instructions.utf8.count
// Convert non-system messages to Chat.Message Self.debugGenerationSettingsEventHandler?(
for msg in request.messages where msg.role != "system" { DebugGenerationSettingsEvent(requestId: requestId, modelId: currentModelRepoId, settings: generationSettings)
let role: Chat.Message.Role = switch msg.role { )
case "assistant": .assistant
case "tool": .user
default: .user
}
var text = msg.content?.textContent ?? "" if preparedPrompt.containsImages, currentModel?.supportsImages != true {
// Format tool_call_id responses as tool_output for the model
if msg.role == "tool" {
if isQwen {
// Qwen expects tool results as-is in a user message
// (the role is already mapped to .user above)
} else {
// Gemma expects tool results wrapped in ```tool_output``` blocks
text = "```tool_output\n\(text)\n```"
}
}
// Format assistant tool_calls back into model-native format
if msg.role == "assistant", let toolCalls = msg.tool_calls, !toolCalls.isEmpty {
let formattedCalls: String
if isQwen {
formattedCalls = ToolPromptBuilder.formatQwenToolCalls(toolCalls)
} else {
formattedCalls = ToolPromptBuilder.formatGemmaToolCalls(toolCalls)
}
text = (text.isEmpty ? "" : text + "\n") + formattedCalls
}
// Extract base64 images from content parts
let imageURLs = msg.content?.imageURLs ?? []
var messageImages: [UserInput.Image] = []
var messageImageBytes = 0
for urlString in imageURLs {
if let decoded = decodeBase64Image(urlString) {
messageImages.append(decoded.image)
messageImageBytes += decoded.estimatedBytes
}
}
// Attach images to this specific message
chatMessages.append(Chat.Message(role: role, content: text, images: messageImages))
messageSignatures.append(
Self.messageSignature(role: role, content: text, imageURLs: imageURLs)
)
estimatedBytes += text.utf8.count + messageImageBytes
images.append(contentsOf: messageImages)
}
if !images.isEmpty, currentModel?.supportsImages != true {
LiveCounters.shared.requestCompleted(requestId: requestId, generationTokens: 0) LiveCounters.shared.requestCompleted(requestId: requestId, generationTokens: 0)
sendResponse( sendResponse(
connection: connection, connection: connection,
@@ -314,7 +318,7 @@ final class APIServer {
} }
// Context window check: estimate token count and reject if over limit // Context window check: estimate token count and reject if over limit
let estimatedPromptTokens = (instructions.count + chatMessages.reduce(0) { $0 + $1.content.count }) * 10 / 35 let estimatedPromptTokens = preparedPrompt.estimatedPromptTokens
if contextLength > 0 { if contextLength > 0 {
let needed = estimatedPromptTokens + maxTokens let needed = estimatedPromptTokens + maxTokens
if needed > contextLength { if needed > contextLength {
@@ -333,195 +337,139 @@ final class APIServer {
let generateParams = GenerateParameters( let generateParams = GenerateParameters(
maxTokens: maxTokens, maxTokens: maxTokens,
temperature: Float(temperature), temperature: Float(generationSettings.temperature),
topP: Float(topP) topP: Float(generationSettings.topP),
topK: generationSettings.topK,
minP: Float(generationSettings.minP),
repetitionPenalty: generationSettings.repetitionPenalty.map(Float.init),
repetitionContextSize: 128,
presencePenalty: generationSettings.presencePenalty.map(Float.init),
presenceContextSize: 128,
frequencyPenalty: generationSettings.frequencyPenalty.map(Float.init),
frequencyContextSize: 128
) )
// Feed all messages except the last as history, then send the last as the prompt
let allButLast = Array(chatMessages.dropLast())
let lastMessage = chatMessages.last ?? Chat.Message(role: .user, content: "")
let historySignatures = Array(messageSignatures.dropLast())
let currentModelId = modelManager.currentModel?.id ?? modelName let currentModelId = modelManager.currentModel?.id ?? modelName
let lease = ConversationSessionCache.shared.checkoutSession( let engine = InferenceEngine(container: container)
modelId: currentModelId, let preparedInference: InferenceEngine.PreparedInference
instructions: instructions, do {
historySignatures: historySignatures, let prepareStartedAt = Date()
requestMessageCount: chatMessages.count, preparedInference = try await engine.prepare(
estimatedPromptTokens: estimatedPromptTokens, preparedPrompt.userInput,
estimatedBytes: estimatedBytes imageFingerprints: preparedPrompt.imageFingerprints
) )
if preparedPrompt.containsImages {
let session: ChatSession LiveCounters.shared.visionProcessingCompleted(
if let reusableSession = lease.session { requestId: requestId,
print("[APIServer] Reusing cached session (\(allButLast.count) history messages)") duration: Date().timeIntervalSince(prepareStartedAt)
session = reusableSession
session.generateParameters = generateParams
ConversationSessionCache.shared.markPrefilling(entryId: lease.entryId)
LiveCounters.shared.requestPhaseChanged(requestId: requestId, phase: .prefilling)
} else {
print("[APIServer] Creating fresh session")
ConversationSessionCache.shared.markSessionBuild(entryId: lease.entryId)
LiveCounters.shared.requestPhaseChanged(requestId: requestId, phase: .sessionBuild)
// Use `instructions:` for system/tool prompt (matches internal chat pattern).
// Only conversation turns go in `history:` — this avoids replaying the
// large tool prompt as history on every new session.
let instr = instructions.isEmpty ? nil : instructions
let thinkingContext: [String: any Sendable]? = Preferences.enableThinking
? nil
: ["enable_thinking": false]
if !allButLast.isEmpty {
session = ChatSession(
container,
instructions: instr,
history: allButLast,
generateParameters: generateParams,
additionalContext: thinkingContext
)
} else {
session = ChatSession(
container,
instructions: instr,
generateParameters: generateParams,
additionalContext: thinkingContext
) )
} }
ConversationSessionCache.shared.markPrefilling(entryId: lease.entryId) } catch {
LiveCounters.shared.requestPhaseChanged(requestId: requestId, phase: .prefilling) LiveCounters.shared.requestCompleted(requestId: requestId, generationTokens: 0)
sendResponse(connection: connection, status: 500, body: #"{"error":"\#(error.localizedDescription)"}"#)
return
} }
// Extract images from the last message only (ChatSession.streamDetails takes images separately) let cacheKey = preparedInference.cacheKey
let lastImages = lastMessage.images let lease = TokenPrefixCache.shared.lookup(cacheKey: cacheKey, modelId: currentModelId)
let result: (promptTokens: Int, completionTokens: Int, assistantHistoryText: String?, succeeded: Bool) Self.debugLookupEventHandler?(
DebugLookupEvent(
requestId: requestId,
modelId: currentModelId,
promptTokenCount: preparedInference.tokens.count,
isHit: lease.isHit,
matchedTokenCount: lease.matchedTokenCount
)
)
LiveCounters.shared.recordPrefillReuse(
requestId: requestId,
matchedPromptTokens: lease.matchedTokenCount,
promptTokenCount: preparedInference.tokens.count
)
LiveCounters.shared.requestPhaseChanged(requestId: requestId, phase: .prefilling)
let cancellation = CancellationToken()
registerActiveRequest(requestId: requestId, connection: connection, cancellation: cancellation)
defer {
unregisterActiveRequest(requestId: requestId)
}
let streamHandle: InferenceEngine.StreamHandle
do {
streamHandle = try await engine.stream(
InferenceEngine.InferenceRequest(
input: preparedInference.lmInput,
tokens: preparedInference.tokens,
parameters: generateParams,
cachedKV: lease.kvCache,
cachedTokenCount: lease.matchedTokenCount
),
cancellation: cancellation
)
} catch {
LiveCounters.shared.requestCompleted(requestId: requestId, generationTokens: 0)
sendResponse(connection: connection, status: 500, body: #"{"error":"\#(error.localizedDescription)"}"#)
return
}
let result: GenerationOutcome
if isStream { if isStream {
result = await handleStreamingResponse( result = await handleStreamingResponse(
connection: connection, connection: connection,
requestId: requestId, requestId: requestId,
cacheEntryId: lease.entryId, cancellation: cancellation,
session: session, stream: streamHandle.stream,
prompt: lastMessage.content,
images: lastImages,
tools: request.tools, tools: request.tools,
created: created, created: created,
modelName: modelName, modelName: modelName
isQwen: isQwen
) )
} else { } else {
result = await handleNonStreamingResponse( result = await handleNonStreamingResponse(
connection: connection, connection: connection,
requestId: requestId, requestId: requestId,
cacheEntryId: lease.entryId, stream: streamHandle.stream,
session: session,
prompt: lastMessage.content,
images: lastImages,
tools: request.tools, tools: request.tools,
created: created, created: created,
modelName: modelName, modelName: modelName
isQwen: isQwen
) )
} }
if result.succeeded { if !isShuttingDown,
var cachedSignatures = messageSignatures result.succeeded || result.cancelled {
if let assistantHistoryText = result.assistantHistoryText { Self.storePromptCache(
cachedSignatures.append( streamHandle.workingCache,
Self.messageSignature(role: .assistant, content: assistantHistoryText, imageURLs: []) promptTokenCount: preparedInference.tokens.count,
)
}
ConversationSessionCache.shared.completeRequest(
entryId: lease.entryId, entryId: lease.entryId,
session: session, cacheKey: cacheKey,
requestMessageSignatures: cachedSignatures, modelId: currentModelId
requestMessageCount: cachedSignatures.count,
estimatedPromptTokens: estimatedPromptTokens,
estimatedBytes: estimatedBytes,
promptTokens: result.promptTokens,
completionTokens: result.completionTokens
) )
} else {
ConversationSessionCache.shared.abandonRequest(entryId: lease.entryId)
} }
LiveCounters.shared.requestCompleted(requestId: requestId, generationTokens: result.completionTokens) LiveCounters.shared.requestCompleted(requestId: requestId, generationTokens: result.completionTokens)
modelManager.touchActivity() modelManager.touchActivity()
} }
/// Decode a base64 data URI (data:image/png;base64,...) into a UserInput.Image.
private func decodeBase64Image(_ urlString: String) -> DecodedImage? {
// Handle data URIs: data:image/png;base64,<data>
let base64String: String
if urlString.hasPrefix("data:") {
guard let commaIndex = urlString.firstIndex(of: ",") else { return nil }
base64String = String(urlString[urlString.index(after: commaIndex)...])
} else {
// Could be a plain base64 string
base64String = urlString
}
guard let data = Data(base64Encoded: base64String),
let nsImage = NSImage(data: data),
let cgImage = nsImage.cgImage(forProposedRect: nil, context: nil, hints: nil) else {
return nil
}
let estimatedBytes = max(data.count, cgImage.width * cgImage.height * 4)
return DecodedImage(image: .ciImage(CIImage(cgImage: cgImage)), estimatedBytes: estimatedBytes)
}
// MARK: - Non-streaming response // MARK: - Non-streaming response
private func handleNonStreamingResponse( private func handleNonStreamingResponse(
connection: NWConnection, connection: NWConnection,
requestId: String, requestId: String,
cacheEntryId: UUID, stream: AsyncStream<Generation>,
session: ChatSession,
prompt: String,
images: [UserInput.Image],
tools: [APIToolDefinition]?, tools: [APIToolDefinition]?,
created: Int, created: Int,
modelName: String, modelName: String
isQwen: Bool ) async -> GenerationOutcome {
) async -> (promptTokens: Int, completionTokens: Int, assistantHistoryText: String?, succeeded: Bool) {
do { do {
var fullText = "" let outcome = await Self.collectGenerationOutcome(
var promptTokens = 0 stream: stream,
var completionTokens = 0 requestId: requestId,
var frameworkToolCalls: [MLXLMCommon.ToolCall] = [] cancellation: nil
let stream = session.streamDetails(
to: prompt,
images: images,
videos: []
) )
for try await generation in stream {
switch generation {
case .chunk(let text):
fullText += text
completionTokens += 1
LiveCounters.shared.tokenGenerated(tokensPerSecond: 0, totalGenerated: completionTokens)
case .info(let info):
promptTokens = info.promptTokenCount
completionTokens = info.generationTokenCount
ConversationSessionCache.shared.markGenerating(
entryId: cacheEntryId,
promptTokens: promptTokens,
completionTokens: completionTokens
)
LiveCounters.shared.prefillCompleted(requestId: requestId, promptTokens: promptTokens)
if info.tokensPerSecond > 0 {
LiveCounters.shared.tokenGenerated(tokensPerSecond: info.tokensPerSecond, totalGenerated: completionTokens)
}
case .toolCall(let call):
frameworkToolCalls.append(call)
}
}
let resolved = Self.resolveAssistantResponse( let resolved = Self.resolveAssistantResponse(
fullText: fullText, fullText: outcome.fullText,
frameworkToolCalls: frameworkToolCalls, frameworkToolCalls: outcome.frameworkToolCalls,
tools: tools tools: tools
) )
@@ -542,24 +490,26 @@ final class APIServer {
) )
], ],
usage: APIUsageInfo( usage: APIUsageInfo(
prompt_tokens: promptTokens, prompt_tokens: outcome.promptTokens,
completion_tokens: completionTokens, completion_tokens: outcome.completionTokens,
total_tokens: promptTokens + completionTokens total_tokens: outcome.promptTokens + outcome.completionTokens
) )
) )
if let json = try? JSONEncoder().encode(response) { if let json = try? JSONEncoder().encode(response) {
sendResponse(connection: connection, status: 200, body: String(data: json, encoding: .utf8) ?? "{}") sendResponse(connection: connection, status: 200, body: String(data: json, encoding: .utf8) ?? "{}")
} }
let assistantHistoryText = Self.normalizedAssistantHistoryContent( return GenerationOutcome(
content: resolved.content, promptTokens: outcome.promptTokens,
toolCalls: resolved.toolCalls, completionTokens: outcome.completionTokens,
isQwen: isQwen fullText: outcome.fullText,
frameworkToolCalls: outcome.frameworkToolCalls,
succeeded: true,
cancelled: false
) )
return (promptTokens, completionTokens, assistantHistoryText, true)
} catch { } catch {
sendResponse(connection: connection, status: 500, body: #"{"error":"\#(error.localizedDescription)"}"#) sendResponse(connection: connection, status: 500, body: #"{"error":"\#(error.localizedDescription)"}"#)
return (0, 0, nil, false) return GenerationOutcome(promptTokens: 0, completionTokens: 0, fullText: "", frameworkToolCalls: [], succeeded: false, cancelled: false)
} }
} }
@@ -568,15 +518,12 @@ final class APIServer {
private func handleStreamingResponse( private func handleStreamingResponse(
connection: NWConnection, connection: NWConnection,
requestId: String, requestId: String,
cacheEntryId: UUID, cancellation: CancellationToken,
session: ChatSession, stream: AsyncStream<Generation>,
prompt: String,
images: [UserInput.Image],
tools: [APIToolDefinition]?, tools: [APIToolDefinition]?,
created: Int, created: Int,
modelName: String, modelName: String
isQwen: Bool ) async -> GenerationOutcome {
) async -> (promptTokens: Int, completionTokens: Int, assistantHistoryText: String?, succeeded: Bool) {
// Send SSE headers // Send SSE headers
let header = [ let header = [
"HTTP/1.1 200 OK", "HTTP/1.1 200 OK",
@@ -589,55 +536,35 @@ final class APIServer {
].joined(separator: "\r\n") ].joined(separator: "\r\n")
await Self.sendData(connection: connection, data: header.data(using: .utf8)!) await Self.sendData(connection: connection, data: header.data(using: .utf8)!)
connection.stateUpdateHandler = { state in
switch state {
case .cancelled, .failed:
LiveCounters.shared.disconnectDetected(requestId: requestId)
cancellation.cancel()
default:
break
}
}
// Send initial role chunk let encoder = StreamingSSEEncoder(requestId: requestId, created: created, modelName: modelName)
await Self.sendSSEEvent(connection: connection, chunk: APIChatCompletionChunk( await Self.sendData(connection: connection, data: encoder.encodeRoleDelta("assistant"))
id: requestId,
object: "chat.completion.chunk",
created: created,
model: modelName,
choices: [APIStreamChoice(index: 0, delta: APIDeltaMessage(role: "assistant", content: nil, tool_calls: nil), finish_reason: nil)],
usage: nil
))
let hasTools = tools != nil && !(tools?.isEmpty ?? true) let result = await Self.runStreamingLoop(
connection: connection,
// Run the generation loop OFF MainActor. stream: stream,
// ChatSession and NWConnection don't need MainActor. cancellation: cancellation,
// Running on MainActor caused every token to compete with SwiftUI requestId: requestId,
// rendering, creating back-pressure that coalesced all output. encoder: encoder
let stream = session.streamDetails(
to: prompt,
images: images,
videos: []
) )
// Transfer non-Sendable values to the nonisolated loop.
// Safe because we don't touch session/images again until after the loop.
let result = await {
nonisolated(unsafe) let stream = stream
return await Self.runStreamingLoop(
connection: connection,
stream: stream,
requestId: requestId,
created: created,
modelName: modelName
)
}()
let (promptTokens, completionTokens, fullText, frameworkToolCalls, succeeded) = result if result.cancelled {
connection.cancel()
if promptTokens > 0 { return result
ConversationSessionCache.shared.markGenerating(
entryId: cacheEntryId,
promptTokens: promptTokens,
completionTokens: completionTokens
)
LiveCounters.shared.prefillCompleted(requestId: requestId, promptTokens: promptTokens)
} }
let resolved = Self.resolveAssistantResponse( let resolved = Self.resolveAssistantResponse(
fullText: fullText, fullText: result.fullText,
frameworkToolCalls: frameworkToolCalls, frameworkToolCalls: result.frameworkToolCalls,
tools: tools tools: tools
) )
@@ -662,21 +589,16 @@ final class APIServer {
model: modelName, model: modelName,
choices: [APIStreamChoice(index: 0, delta: APIDeltaMessage(role: nil, content: nil, tool_calls: nil), finish_reason: resolved.finishReason)], choices: [APIStreamChoice(index: 0, delta: APIDeltaMessage(role: nil, content: nil, tool_calls: nil), finish_reason: resolved.finishReason)],
usage: APIUsageInfo( usage: APIUsageInfo(
prompt_tokens: promptTokens, prompt_tokens: result.promptTokens,
completion_tokens: completionTokens, completion_tokens: result.completionTokens,
total_tokens: promptTokens + completionTokens total_tokens: result.promptTokens + result.completionTokens
) )
)) ))
// Send [DONE] and close // Send [DONE] and close
await Self.sendData(connection: connection, data: "data: [DONE]\n\n".data(using: .utf8)!) await Self.sendData(connection: connection, data: "data: [DONE]\n\n".data(using: .utf8)!)
connection.cancel() connection.cancel()
let assistantHistoryText = Self.normalizedAssistantHistoryContent( return result
content: resolved.content,
toolCalls: resolved.toolCalls,
isQwen: isQwen
)
return (promptTokens, completionTokens, assistantHistoryText, succeeded)
} }
/// Run the token generation + SSE send loop entirely off MainActor. /// Run the token generation + SSE send loop entirely off MainActor.
@@ -684,54 +606,20 @@ final class APIServer {
/// multiple actor hops competing with SwiftUI, causing all output to batch. /// multiple actor hops competing with SwiftUI, causing all output to batch.
nonisolated private static func runStreamingLoop( nonisolated private static func runStreamingLoop(
connection: NWConnection, connection: NWConnection,
stream: AsyncThrowingStream<Generation, any Error>, stream: AsyncStream<Generation>,
cancellation: CancellationToken,
requestId: String, requestId: String,
created: Int, encoder: StreamingSSEEncoder
modelName: String ) async -> GenerationOutcome {
) async -> (Int, Int, String, [MLXLMCommon.ToolCall], Bool) { var outcome = await collectGenerationOutcome(
var promptTokens = 0 stream: stream,
var completionTokens = 0 requestId: requestId,
var fullText = "" cancellation: cancellation
var frameworkToolCalls: [MLXLMCommon.ToolCall] = [] ) { text in
await sendData(connection: connection, data: encoder.encodeContentDelta(text))
do {
for try await generation in stream {
switch generation {
case .chunk(let text):
completionTokens += 1
fullText += text
// Update live counters directly — no MainActor hop needed
LiveCounters.shared.tokenGenerated(tokensPerSecond: 0, totalGenerated: completionTokens)
// Send directly — no MainActor hop.
await sendSSEEvent(connection: connection, chunk: APIChatCompletionChunk(
id: requestId,
object: "chat.completion.chunk",
created: created,
model: modelName,
choices: [APIStreamChoice(index: 0, delta: APIDeltaMessage(role: nil, content: text, tool_calls: nil), finish_reason: nil)],
usage: nil
))
case .info(let info):
promptTokens = info.promptTokenCount
completionTokens = info.generationTokenCount
if info.tokensPerSecond > 0 {
LiveCounters.shared.tokenGenerated(tokensPerSecond: info.tokensPerSecond, totalGenerated: completionTokens)
}
case .toolCall(let call):
frameworkToolCalls.append(call)
}
}
} catch {
let errorEvent = "data: {\"error\":\"\(error.localizedDescription)\"}\n\n"
await sendData(connection: connection, data: errorEvent.data(using: .utf8)!)
return (promptTokens, completionTokens, fullText, frameworkToolCalls, false)
} }
outcome.succeeded = !outcome.cancelled
return (promptTokens, completionTokens, fullText, frameworkToolCalls, true) return outcome
} }
/// Send an SSE event and wait for the protocol stack to process it. /// Send an SSE event and wait for the protocol stack to process it.
@@ -751,6 +639,93 @@ final class APIServer {
} }
} }
nonisolated private static func collectGenerationOutcome(
stream: AsyncStream<Generation>,
requestId: String,
cancellation: CancellationToken?,
onChunk: ((String) async -> Void)? = nil
) async -> GenerationOutcome {
var promptTokens = 0
var completionTokens = 0
var fullText = ""
var frameworkToolCalls: [MLXLMCommon.ToolCall] = []
var cancelled = false
var sawFirstChunk = false
for await generation in stream {
if let cancellation, cancellation.isCancelled {
cancelled = true
break
}
switch generation {
case .chunk(let text):
if !sawFirstChunk {
sawFirstChunk = true
LiveCounters.shared.firstTokenGenerated(requestId: requestId)
}
completionTokens += 1
fullText += text
LiveCounters.shared.tokenGenerated(tokensPerSecond: 0, totalGenerated: completionTokens)
if let onChunk {
await onChunk(text)
}
case .info(let info):
promptTokens = info.promptTokenCount
completionTokens = info.generationTokenCount
LiveCounters.shared.prefillCompleted(requestId: requestId, promptTokens: promptTokens)
if info.tokensPerSecond > 0 {
LiveCounters.shared.tokenGenerated(tokensPerSecond: info.tokensPerSecond, totalGenerated: completionTokens)
}
case .toolCall(let call):
frameworkToolCalls.append(call)
}
}
return GenerationOutcome(
promptTokens: promptTokens,
completionTokens: completionTokens,
fullText: fullText,
frameworkToolCalls: frameworkToolCalls,
succeeded: !cancelled,
cancelled: cancelled
)
}
private static func storePromptCache(
_ cache: [KVCache],
promptTokenCount: Int,
entryId: UUID,
cacheKey: [Int],
modelId: String
) {
guard trimGeneratedTokens(cache, promptTokenCount: promptTokenCount) else {
return
}
TokenPrefixCache.shared.store(
entryId: entryId,
kvCache: cache,
cacheKey: cacheKey,
modelId: modelId
)
}
private static func trimGeneratedTokens(_ cache: [KVCache], promptTokenCount: Int) -> Bool {
for layer in cache {
let excess = layer.offset - promptTokenCount
guard excess <= 0 || layer.isTrimmable else {
return false
}
if excess > 0 {
let trimmed = layer.trim(excess)
guard trimmed == excess else {
return false
}
}
}
return true
}
// MARK: - HTTP helpers // MARK: - HTTP helpers
private func sendResponse( private func sendResponse(
@@ -839,7 +814,7 @@ final class APIServer {
return text.isEmpty ? nil : text return text.isEmpty ? nil : text
} }
private static func resolveAssistantResponse( static func resolveAssistantResponse(
fullText: String, fullText: String,
frameworkToolCalls: [MLXLMCommon.ToolCall], frameworkToolCalls: [MLXLMCommon.ToolCall],
tools: [APIToolDefinition]? tools: [APIToolDefinition]?
@@ -887,9 +862,13 @@ final class APIServer {
} }
} }
private struct DecodedImage { private struct GenerationOutcome {
let image: UserInput.Image var promptTokens: Int
let estimatedBytes: Int var completionTokens: Int
var fullText: String
var frameworkToolCalls: [MLXLMCommon.ToolCall]
var succeeded: Bool
var cancelled: Bool
} }
// MARK: - HTTP request parser // MARK: - HTTP request parser

14
MLXServer/Server/CancellationToken.swift Normal file
View File

@@ -0,0 +1,14 @@
import os
/// Thread-safe cancellation flag for cooperative stream shutdown.
final class CancellationToken: @unchecked Sendable {
private let lock = OSAllocatedUnfairLock(initialState: false)
var isCancelled: Bool {
lock.withLock { $0 }
}
func cancel() {
lock.withLock { $0 = true }
}
}

358
MLXServer/Server/ConversationSessionCache.swift
View File

@@ -1,358 +0,0 @@
import Foundation
import MLXLMCommon
import os
enum APISessionPhase: String, Sendable {
case idle = "Idle"
case sessionBuild = "Session Build"
case prefilling = "Prefilling"
case generating = "Generating"
}
/// Bounded cache of API chat sessions keyed by normalized conversation history.
/// The cache is internal-only and safe to sample from the monitor without involving MainActor.
final class ConversationSessionCache: @unchecked Sendable {
static let shared = ConversationSessionCache()
private let lock = OSAllocatedUnfairLock()
private let maxEntries = 8
private let maxCachedTokens = 256_000
private let idleTTL: TimeInterval = 10 * 60
private var entries: [UUID: Entry] = [:]
private var totals = Totals()
private init() {}
struct Lease {
let entryId: UUID
let session: ChatSession?
let reusedPromptTokens: Int
let cacheHit: Bool
}
struct SessionSummary: Identifiable, Sendable {
let id: UUID
let modelId: String
let phase: APISessionPhase
let messageCount: Int
let cachedTokenEstimate: Int
let estimatedBytes: Int
let inFlightRequests: Int
let hitCount: Int
let lastPromptTokens: Int
let lastCompletionTokens: Int
let lastReuseTokens: Int
let createdAt: Date
let lastAccessAt: Date
}
struct Snapshot: Sendable {
let totalEntries: Int
let warmEntries: Int
let activeEntries: Int
let generatingEntries: Int
let estimatedBytes: Int
let cachedTokenEstimate: Int
let totalHits: Int
let totalMisses: Int
let totalEvictions: Int
let totalReusePromptTokens: Int
let totalRebuildPromptTokens: Int
let sessions: [SessionSummary]
}
func checkoutSession(
modelId: String,
instructions: String,
historySignatures: [UInt64],
requestMessageCount: Int,
estimatedPromptTokens: Int,
estimatedBytes: Int
) -> Lease {
lock.lock()
let now = Date()
pruneExpiredLocked(now: now)
let instructionsHash = Self.stableHash(instructions)
let match = entries
.values
.filter {
$0.modelId == modelId
&& $0.instructionsHash == instructionsHash
&& $0.session != nil
&& $0.inFlightRequests == 0
&& Self.historyMatches(cached: $0.requestMessageSignatures, incoming: historySignatures)
}
.max { lhs, rhs in
lhs.requestMessageSignatures.count < rhs.requestMessageSignatures.count
}
if let match {
var entry = match
entry.inFlightRequests += 1
entry.lastAccessAt = now
entry.phase = .prefilling
entry.lastReuseTokens = max(entry.cachedTokenEstimate, estimatedPromptTokens)
entry.hitCount += 1
entries[entry.id] = entry
totals.totalHits += 1
totals.totalReusePromptTokens += entry.lastReuseTokens
let lease = Lease(
entryId: entry.id,
session: entry.session,
reusedPromptTokens: entry.lastReuseTokens,
cacheHit: true
)
lock.unlock()
return lease
}
let entryId = UUID()
entries[entryId] = Entry(
id: entryId,
modelId: modelId,
instructionsHash: instructionsHash,
requestMessageSignatures: historySignatures,
messageCount: requestMessageCount,
cachedTokenEstimate: estimatedPromptTokens,
estimatedBytes: estimatedBytes,
createdAt: now,
lastAccessAt: now,
inFlightRequests: 1,
hitCount: 0,
phase: .sessionBuild,
lastPromptTokens: 0,
lastCompletionTokens: 0,
lastReuseTokens: 0,
session: nil
)
totals.totalMisses += 1
totals.totalRebuildPromptTokens += estimatedPromptTokens
lock.unlock()
return Lease(entryId: entryId, session: nil, reusedPromptTokens: 0, cacheHit: false)
}
func markSessionBuild(entryId: UUID) {
updatePhase(entryId: entryId, phase: .sessionBuild)
}
func markPrefilling(entryId: UUID) {
updatePhase(entryId: entryId, phase: .prefilling)
}
func markGenerating(entryId: UUID, promptTokens: Int, completionTokens: Int) {
lock.lock()
if var entry = entries[entryId] {
entry.phase = .generating
entry.lastPromptTokens = promptTokens
entry.lastCompletionTokens = completionTokens
entry.cachedTokenEstimate = max(entry.cachedTokenEstimate, promptTokens + completionTokens)
entry.lastAccessAt = Date()
entries[entryId] = entry
}
lock.unlock()
}
func completeRequest(
entryId: UUID,
session: ChatSession,
requestMessageSignatures: [UInt64],
requestMessageCount: Int,
estimatedPromptTokens: Int,
estimatedBytes: Int,
promptTokens: Int,
completionTokens: Int
) {
lock.lock()
let now = Date()
if var entry = entries[entryId] {
entry.session = session
entry.requestMessageSignatures = requestMessageSignatures
entry.messageCount = requestMessageCount
entry.cachedTokenEstimate = max(estimatedPromptTokens, promptTokens + completionTokens)
entry.estimatedBytes = estimatedBytes
entry.lastPromptTokens = promptTokens
entry.lastCompletionTokens = completionTokens
entry.lastAccessAt = now
entry.inFlightRequests = max(0, entry.inFlightRequests - 1)
entry.phase = .idle
entries[entryId] = entry
enforceBudgetLocked(now: now)
}
lock.unlock()
}
func abandonRequest(entryId: UUID) {
lock.lock()
if var entry = entries[entryId] {
entry.inFlightRequests = max(0, entry.inFlightRequests - 1)
if entry.session == nil && entry.inFlightRequests == 0 {
entries.removeValue(forKey: entryId)
} else {
entry.phase = .idle
entry.lastAccessAt = Date()
entries[entryId] = entry
}
}
lock.unlock()
}
func invalidateAll() {
lock.lock()
totals.totalEvictions += entries.count
entries.removeAll()
lock.unlock()
}
func reset() {
lock.lock()
entries.removeAll()
totals = Totals()
lock.unlock()
}
func snapshot() -> Snapshot {
lock.lock()
let now = Date()
pruneExpiredLocked(now: now)
let allEntries = Array(entries.values)
let sessions = allEntries
.sorted {
if $0.inFlightRequests != $1.inFlightRequests {
return $0.inFlightRequests > $1.inFlightRequests
}
return $0.lastAccessAt > $1.lastAccessAt
}
.map {
SessionSummary(
id: $0.id,
modelId: $0.modelId,
phase: $0.phase,
messageCount: $0.messageCount,
cachedTokenEstimate: $0.cachedTokenEstimate,
estimatedBytes: $0.estimatedBytes,
inFlightRequests: $0.inFlightRequests,
hitCount: $0.hitCount,
lastPromptTokens: $0.lastPromptTokens,
lastCompletionTokens: $0.lastCompletionTokens,
lastReuseTokens: $0.lastReuseTokens,
createdAt: $0.createdAt,
lastAccessAt: $0.lastAccessAt
)
}
let snapshot = Snapshot(
totalEntries: allEntries.count,
warmEntries: allEntries.filter { $0.session != nil }.count,
activeEntries: allEntries.filter { $0.inFlightRequests > 0 }.count,
generatingEntries: allEntries.filter { $0.phase == .generating }.count,
estimatedBytes: allEntries.reduce(0) { $0 + $1.estimatedBytes },
cachedTokenEstimate: allEntries.reduce(0) { $0 + $1.cachedTokenEstimate },
totalHits: totals.totalHits,
totalMisses: totals.totalMisses,
totalEvictions: totals.totalEvictions,
totalReusePromptTokens: totals.totalReusePromptTokens,
totalRebuildPromptTokens: totals.totalRebuildPromptTokens,
sessions: sessions
)
lock.unlock()
return snapshot
}
private func updatePhase(entryId: UUID, phase: APISessionPhase) {
lock.lock()
if var entry = entries[entryId] {
entry.phase = phase
entry.lastAccessAt = Date()
entries[entryId] = entry
}
lock.unlock()
}
private func pruneExpiredLocked(now: Date) {
let expired = entries.values.filter {
$0.inFlightRequests == 0 && now.timeIntervalSince($0.lastAccessAt) > idleTTL
}
guard !expired.isEmpty else { return }
for entry in expired {
entries.removeValue(forKey: entry.id)
}
totals.totalEvictions += expired.count
}
private func enforceBudgetLocked(now: Date) {
pruneExpiredLocked(now: now)
func totalCachedTokens() -> Int {
entries.values.reduce(0) { $0 + $1.cachedTokenEstimate }
}
while entries.count > maxEntries || totalCachedTokens() > maxCachedTokens {
guard let victim = entries.values
.filter({ $0.inFlightRequests == 0 })
.sorted(by: evictionOrder)
.first
else {
break
}
entries.removeValue(forKey: victim.id)
totals.totalEvictions += 1
}
}
private func evictionOrder(lhs: Entry, rhs: Entry) -> Bool {
if lhs.lastAccessAt != rhs.lastAccessAt {
return lhs.lastAccessAt < rhs.lastAccessAt
}
if lhs.cachedTokenEstimate != rhs.cachedTokenEstimate {
return lhs.cachedTokenEstimate > rhs.cachedTokenEstimate
}
return lhs.createdAt < rhs.createdAt
}
private static func historyMatches(cached: [UInt64], incoming: [UInt64]) -> Bool {
guard cached.count <= incoming.count,
incoming.count <= cached.count + 1 else { return false }
for (lhs, rhs) in zip(cached, incoming) where lhs != rhs {
return false
}
return true
}
static func stableHash(_ text: String) -> UInt64 {
var hash: UInt64 = 14_695_981_039_346_656_037
for byte in text.utf8 {
hash ^= UInt64(byte)
hash &*= 1_099_511_628_211
}
return hash
}
private struct Entry {
let id: UUID
let modelId: String
let instructionsHash: UInt64
var requestMessageSignatures: [UInt64]
var messageCount: Int
var cachedTokenEstimate: Int
var estimatedBytes: Int
let createdAt: Date
var lastAccessAt: Date
var inFlightRequests: Int
var hitCount: Int
var phase: APISessionPhase
var lastPromptTokens: Int
var lastCompletionTokens: Int
var lastReuseTokens: Int
var session: ChatSession?
}
private struct Totals {
var totalHits: Int = 0
var totalMisses: Int = 0
var totalEvictions: Int = 0
var totalReusePromptTokens: Int = 0
var totalRebuildPromptTokens: Int = 0
}
}

31
MLXServer/Server/ImageDecoder.swift Normal file
View File

@@ -0,0 +1,31 @@
import AppKit
import CoreImage
import Foundation
import MLXLMCommon
/// Extracted from APIServer — decodes data URIs to UserInput.Image.
enum ImageDecoder {
struct DecodedImage {
let image: UserInput.Image
let estimatedBytes: Int
}
static func decode(_ urlString: String) -> DecodedImage? {
let base64String: String
if urlString.hasPrefix("data:") {
guard let commaIndex = urlString.firstIndex(of: ",") else { return nil }
base64String = String(urlString[urlString.index(after: commaIndex)...])
} else {
base64String = urlString
}
guard let data = Data(base64Encoded: base64String),
let nsImage = NSImage(data: data),
let cgImage = nsImage.cgImage(forProposedRect: nil, context: nil, hints: nil) else {
return nil
}
let estimatedBytes = max(data.count, cgImage.width * cgImage.height * 4)
return DecodedImage(image: .ciImage(CIImage(cgImage: cgImage)), estimatedBytes: estimatedBytes)
}
}

227
MLXServer/Server/InferenceEngine.swift Normal file
View File

@@ -0,0 +1,227 @@
import MLX
import MLXLMCommon
/// Stateless inference wrapper for the API path.
final class InferenceEngine: @unchecked Sendable {
private let container: ModelContainer
init(container: ModelContainer) {
self.container = container
}
struct InferenceRequest: @unchecked Sendable {
let input: LMInput
let tokens: [Int]
let parameters: GenerateParameters
let cachedKV: [KVCache]?
let cachedTokenCount: Int
}
struct StreamHandle: @unchecked Sendable {
let stream: AsyncStream<Generation>
let workingCache: [KVCache]
}
struct PreparedInference: @unchecked Sendable {
let lmInput: LMInput
let tokens: [Int]
let cacheKey: [Int]
let hasImages: Bool
}
func stream(
_ request: InferenceRequest,
cancellation: CancellationToken
) async throws -> StreamHandle {
_ = cancellation
nonisolated(unsafe) let input = request.input
nonisolated(unsafe) let cachedKV = request.cachedKV
let parameters = request.parameters
return try await container.perform { context in
let workingCache = cachedKV ?? context.model.newCache(parameters: parameters)
let stream = try MLXLMCommon.generate(
input: input,
cache: workingCache,
parameters: parameters,
context: context
)
return StreamHandle(stream: stream, workingCache: workingCache)
}
}
func prepare(_ userInput: UserInput, imageFingerprints: [UInt64] = []) async throws -> PreparedInference {
nonisolated(unsafe) let input = userInput
let lmInput = try await container.prepare(input: input)
nonisolated(unsafe) let preparedInput = lmInput
let tokenArray: [Int] = await container.perform { _ in
preparedInput.text.tokens.asArray(Int.self)
}
let cacheKey = await buildCacheKey(tokens: tokenArray, imageFingerprints: imageFingerprints)
return PreparedInference(
lmInput: lmInput,
tokens: tokenArray,
cacheKey: cacheKey,
hasImages: userInput.images.count > 0
)
}
private func buildCacheKey(tokens: [Int], imageFingerprints: [UInt64]) async -> [Int] {
guard !imageFingerprints.isEmpty else {
return tokens
}
let modelIdentifier = await container.configuration.name.lowercased()
if modelIdentifier.contains("gemma"),
let key = Self.buildGemmaCacheKey(tokens: tokens, imageFingerprints: imageFingerprints) {
return key
}
return await container.perform { context in
let visionStartTokens = context.tokenizer.encode(text: "<|vision_start|>")
let imagePadTokens = context.tokenizer.encode(text: "<|image_pad|>")
let visionEndTokens = context.tokenizer.encode(text: "<|vision_end|>")
if let key = Self.buildQwenCacheKey(
tokens: tokens,
imageFingerprints: imageFingerprints,
visionStartTokens: visionStartTokens,
imagePadTokens: imagePadTokens,
visionEndTokens: visionEndTokens
) {
return key
}
return Self.buildFallbackVisionCacheKey(tokens: tokens, imageFingerprints: imageFingerprints)
}
}
private static func buildGemmaCacheKey(tokens: [Int], imageFingerprints: [UInt64]) -> [Int]? {
let imageTokenId = 262_144
let totalImageTokenCount = tokens.reduce(into: 0) { count, token in
if token == imageTokenId {
count += 1
}
}
guard totalImageTokenCount > 0,
totalImageTokenCount % imageFingerprints.count == 0
else {
return nil
}
let tokensPerImage = totalImageTokenCount / imageFingerprints.count
guard tokensPerImage > 0 else {
return nil
}
var key: [Int] = []
key.reserveCapacity(tokens.count + imageFingerprints.count * 2)
var currentImageTokenCount = 0
var currentImageIndex = 0
for token in tokens {
key.append(token)
guard token == imageTokenId else { continue }
currentImageTokenCount += 1
if currentImageTokenCount == tokensPerImage,
currentImageIndex < imageFingerprints.count {
key.append(contentsOf: fingerprintSentinels(imageFingerprints[currentImageIndex]))
currentImageIndex += 1
currentImageTokenCount = 0
}
}
guard currentImageIndex == imageFingerprints.count else {
return nil
}
return key
}
private static func buildQwenCacheKey(
tokens: [Int],
imageFingerprints: [UInt64],
visionStartTokens: [Int],
imagePadTokens: [Int],
visionEndTokens: [Int]
) -> [Int]? {
guard !visionStartTokens.isEmpty,
!imagePadTokens.isEmpty,
!visionEndTokens.isEmpty
else {
return nil
}
var key: [Int] = []
key.reserveCapacity(tokens.count + imageFingerprints.count * 2)
var tokenIndex = 0
var imageIndex = 0
while tokenIndex < tokens.count {
if matches(tokens: tokens, sequence: visionStartTokens, at: tokenIndex) {
let imageRegionStart = tokenIndex
var scanIndex = tokenIndex + visionStartTokens.count
var sawImagePad = false
while matches(tokens: tokens, sequence: imagePadTokens, at: scanIndex) {
sawImagePad = true
scanIndex += imagePadTokens.count
}
if sawImagePad,
matches(tokens: tokens, sequence: visionEndTokens, at: scanIndex),
imageIndex < imageFingerprints.count {
let imageRegionEnd = scanIndex + visionEndTokens.count
key.append(contentsOf: tokens[imageRegionStart..<imageRegionEnd])
key.append(contentsOf: fingerprintSentinels(imageFingerprints[imageIndex]))
tokenIndex = imageRegionEnd
imageIndex += 1
continue
}
}
key.append(tokens[tokenIndex])
tokenIndex += 1
}
guard imageIndex == imageFingerprints.count else {
return nil
}
return key
}
private static func buildFallbackVisionCacheKey(tokens: [Int], imageFingerprints: [UInt64]) -> [Int] {
var key: [Int] = []
key.reserveCapacity(tokens.count + imageFingerprints.count * 2)
for fingerprint in imageFingerprints {
key.append(contentsOf: fingerprintSentinels(fingerprint))
}
key.append(contentsOf: tokens)
return key
}
private static func fingerprintSentinels(_ fingerprint: UInt64) -> [Int] {
let upper = Int(UInt32(truncatingIfNeeded: fingerprint >> 32))
let lower = Int(UInt32(truncatingIfNeeded: fingerprint))
return [-(upper + 1), -(lower + 1)]
}
private static func matches(tokens: [Int], sequence: [Int], at start: Int) -> Bool {
guard start + sequence.count <= tokens.count else {
return false
}
for (offset, token) in sequence.enumerated() where tokens[start + offset] != token {
return false
}
return true
}
}

159
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import Foundation
import MLXLMCommon
/// Converts OpenAI-format API messages into reusable prompt artifacts for the API server.
enum PromptBuilder {
struct PreparedPrompt {
let instructions: String
let chatMessages: [Chat.Message]
let messageSignatures: [UInt64]
let imageFingerprints: [UInt64]
let estimatedBytes: Int
let estimatedPromptTokens: Int
let containsImages: Bool
let additionalContext: [String: any Sendable]?
let userInput: UserInput
}
static func build(
from request: APIChatCompletionRequest,
modelId: String,
thinkingEnabled: Bool
) -> PreparedPrompt {
var instructions = ""
for msg in request.messages where msg.role == "system" {
let text = msg.content?.textContent ?? ""
guard !text.isEmpty else { continue }
if !instructions.isEmpty { instructions += "\n\n" }
instructions += text
}
if let tools = request.tools, !tools.isEmpty {
let toolPrompt = ToolPromptBuilder.buildSystemPrompt(tools: tools, modelId: modelId)
if !instructions.isEmpty { instructions += "\n\n" }
instructions += toolPrompt
}
let isQwen = modelId.lowercased().contains("qwen")
var chatMessages: [Chat.Message] = []
var messageSignatures: [UInt64] = []
var imageFingerprints: [UInt64] = []
var estimatedBytes = instructions.utf8.count
var containsImages = false
for msg in request.messages where msg.role != "system" {
let role: Chat.Message.Role = switch msg.role {
case "assistant": .assistant
case "tool": .user
default: .user
}
var text = msg.content?.textContent ?? ""
if msg.role == "tool", !isQwen {
text = "```tool_output\n\(text)\n```"
}
if msg.role == "assistant", let toolCalls = msg.tool_calls, !toolCalls.isEmpty {
let formattedCalls = isQwen
? ToolPromptBuilder.formatQwenToolCalls(toolCalls)
: ToolPromptBuilder.formatGemmaToolCalls(toolCalls)
text = text.isEmpty ? formattedCalls : text + "\n" + formattedCalls
}
let imageURLs = msg.content?.imageURLs ?? []
var messageImages: [UserInput.Image] = []
var messageImageBytes = 0
for urlString in imageURLs {
if let decoded = ImageDecoder.decode(urlString) {
messageImages.append(decoded.image)
imageFingerprints.append(imageFingerprint(urlString))
messageImageBytes += decoded.estimatedBytes
}
}
containsImages = containsImages || !messageImages.isEmpty
chatMessages.append(Chat.Message(role: role, content: text, images: messageImages))
messageSignatures.append(messageSignature(role: role, content: text, imageURLs: imageURLs))
estimatedBytes += text.utf8.count + messageImageBytes
}
let additionalContext: [String: any Sendable]? = thinkingEnabled
? nil
: ["enable_thinking": false]
var allMessages: [Chat.Message] = []
if !instructions.isEmpty {
allMessages.append(Chat.Message(role: .system, content: instructions))
}
allMessages.append(contentsOf: chatMessages)
let allImages = chatMessages.flatMap(\ .images)
let userInput = UserInput(
prompt: .chat(allMessages),
images: allImages,
videos: [],
tools: nil,
additionalContext: additionalContext
)
let estimatedPromptTokens = estimatePromptTokens(instructions: instructions, chatMessages: chatMessages)
return PreparedPrompt(
instructions: instructions,
chatMessages: chatMessages,
messageSignatures: messageSignatures,
imageFingerprints: imageFingerprints,
estimatedBytes: estimatedBytes,
estimatedPromptTokens: estimatedPromptTokens,
containsImages: containsImages,
additionalContext: additionalContext,
userInput: userInput
)
}
static func estimatePromptTokens(instructions: String, chatMessages: [Chat.Message]) -> Int {
let characterCount = instructions.count + chatMessages.reduce(0) { partial, message in
partial + message.content.count
}
return max(0, characterCount * 10 / 35)
}
private static func imageFingerprint(_ source: String) -> UInt64 {
var hash: UInt64 = 14_695_981_039_346_656_037
for byte in source.utf8 {
hash ^= UInt64(byte)
hash &*= 1_099_511_628_211
}
return hash
}
private static func messageSignature(role: Chat.Message.Role, content: String, imageURLs: [String]) -> UInt64 {
var hash: UInt64 = 14_695_981_039_346_656_037
func mix(_ text: String) {
for byte in text.utf8 {
hash ^= UInt64(byte)
hash &*= 1_099_511_628_211
}
}
switch role {
case .assistant:
mix("assistant")
case .system:
mix("system")
case .user:
mix("user")
@unknown default:
mix("unknown")
}
mix("|")
mix(content)
for imageURL in imageURLs {
mix("|")
mix(imageURL)
}
return hash
}
}

72
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import Foundation
/// Pre-computes static JSON parts for SSE streaming.
/// Only the dynamic delta payload is serialized per token.
struct StreamingSSEEncoder: Sendable {
private let requestId: String
private let created: Int
private let modelName: String
init(requestId: String, created: Int, modelName: String) {
self.requestId = requestId
self.created = created
self.modelName = modelName
}
func encodeContentDelta(_ text: String) -> Data {
Self.encodeChunk(
APIChatCompletionChunk(
id: requestId,
object: "chat.completion.chunk",
created: created,
model: modelName,
choices: [
APIStreamChoice(
index: 0,
delta: APIDeltaMessage(role: nil, content: text, tool_calls: nil),
finish_reason: nil
)
],
usage: nil
)
)
}
func encodeRoleDelta(_ role: String) -> Data {
Self.encodeChunk(
APIChatCompletionChunk(
id: requestId,
object: "chat.completion.chunk",
created: created,
model: modelName,
choices: [
APIStreamChoice(
index: 0,
delta: APIDeltaMessage(role: role, content: nil, tool_calls: nil),
finish_reason: nil
)
],
usage: nil
)
)
}
static func encodeFinalChunk(_ chunk: APIChatCompletionChunk) -> Data {
encodeChunk(chunk)
}
private static func encodeChunk(_ chunk: APIChatCompletionChunk) -> Data {
let encoder = JSONEncoder()
encoder.outputFormatting = [.sortedKeys]
guard let json = try? encoder.encode(chunk) else {
return Data("data: {}\n\n".utf8)
}
var data = Data(capacity: json.count + 8)
data.append(Data("data: ".utf8))
data.append(json)
data.append(Data("\n\n".utf8))
return data
}
}

653
MLXServer/Server/TokenPrefixCache.swift Normal file
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import Foundation
import Metal
import MLX
import MLXLMCommon
import os
final class TokenPrefixCache: @unchecked Sendable {
static let shared = TokenPrefixCache()
struct CacheLease: @unchecked Sendable {
let entryId: UUID
let kvCache: [KVCache]?
let matchedTokenCount: Int
let isHit: Bool
}
struct EntrySummary: Identifiable, Sendable {
let id: UUID
let modelId: String
let tokenCount: Int
let estimatedBytes: Int
let createdAt: Date
let lastAccessAt: Date
let hitCount: Int
}
struct Snapshot: Sendable {
let totalEntries: Int
let totalCachedTokens: Int
let estimatedBytes: Int
let memoryBudgetBytes: Int
let memoryUsagePercent: Double
let totalHits: Int
let totalMisses: Int
let totalEvictions: Int
let hitRate: Double
let prefixHits: Int
let supersequenceHits: Int
let lcpHits: Int
let quantizationBytesSaved: Int // Total bytes saved by quantization
let quantizationEnabled: Bool
let entries: [EntrySummary]
}
private final class TrieNode {
var children: [Int: TrieNode] = [:]
var entryId: UUID?
}
private struct CacheEntry {
let id: UUID
let modelId: String
let kvCache: [KVCache]
let tokenCount: Int
let cacheKey: [Int]
let estimatedBytes: Int
let createdAt: Date
var lastAccessAt: Date
var hitCount: Int
let isQuantized: Bool
}
private struct Stats {
var totalHits: Int = 0
var totalMisses: Int = 0
var totalEvictions: Int = 0
var totalPrefixHits: Int = 0
var totalSupersequenceHits: Int = 0
var totalLCPHits: Int = 0
var totalQuantizationBytesSaved: Int = 0
}
struct QuantizationConfig: Sendable {
/// Whether to quantize KV caches for storage
let enabled: Bool
/// Bit width for quantization (8 is recommended for 50% savings with minimal quality loss)
let bits: Int
/// Group size for quantization. Matches mlx-swift-lm default.
let groupSize: Int
/// Minimum token count before quantization applies. Short sequences don't benefit.
let minTokens: Int
static let `default` = QuantizationConfig(
enabled: false,
bits: 8,
groupSize: 64,
minTokens: 256
)
static let aggressive = QuantizationConfig(
enabled: true,
bits: 8,
groupSize: 64,
minTokens: 256
)
}
private let lock = OSAllocatedUnfairLock()
private let maxMemoryBytes: Int
private let idleTTL: TimeInterval
private let estimateBytesProvider: ([KVCache]) -> Int
private let nowProvider: () -> Date
private var root = TrieNode()
private var entries: [UUID: CacheEntry] = [:]
private var currentMemoryBytes: Int = 0
private var stats = Stats()
private var quantizationConfig: QuantizationConfig
private init() {
self.maxMemoryBytes = Self.computeMemoryBudget()
self.idleTTL = 30 * 60
self.estimateBytesProvider = Self.estimateBytes
self.nowProvider = Date.init
self.quantizationConfig = Self.preferencesQuantizationConfig()
}
init(
memoryBudgetBytes: Int,
idleTTL: TimeInterval = 30 * 60,
estimateBytesProvider: @escaping ([KVCache]) -> Int = TokenPrefixCache.estimateBytes,
nowProvider: @escaping () -> Date = Date.init,
quantizationConfig: QuantizationConfig = .default
) {
self.maxMemoryBytes = memoryBudgetBytes
self.idleTTL = idleTTL
self.estimateBytesProvider = estimateBytesProvider
self.nowProvider = nowProvider
self.quantizationConfig = quantizationConfig
}
/// Update quantization configuration.
func setQuantizationConfig(_ config: QuantizationConfig) {
lock.lock()
self.quantizationConfig = config
lock.unlock()
}
/// Get current quantization configuration.
func getQuantizationConfig() -> QuantizationConfig {
lock.lock()
defer { lock.unlock() }
return quantizationConfig
}
private static func preferencesQuantizationConfig() -> QuantizationConfig {
guard Preferences.kvQuantizationEnabled else {
return .default
}
return QuantizationConfig(
enabled: true,
bits: Preferences.kvQuantizationBits,
groupSize: 64,
minTokens: 256
)
}
func lookup(cacheKey: [Int], modelId: String) -> CacheLease {
lock.lock()
let now = nowProvider()
pruneExpiredLocked(now: now)
let queryRealTokenCount = cacheKey.reduce(into: 0) { partialResult, token in
if token >= 0 {
partialResult += 1
}
}
var node = root
var bestMatch: (entryId: UUID, realTokenCount: Int)?
var realTokenCount = 0
var walkedFullKey = true
for key in cacheKey {
guard let child = node.children[key] else {
walkedFullKey = false
break
}
node = child
if key >= 0 { realTokenCount += 1 }
if let entryId = node.entryId,
let entry = entries[entryId],
entry.modelId == modelId {
bestMatch = (entryId: entryId, realTokenCount: realTokenCount)
}
}
if let match = bestMatch,
var entry = entries[match.entryId] {
entry.lastAccessAt = now
entry.hitCount += 1
entries[match.entryId] = entry
removeEntryLocked(entry, countAsEviction: false)
stats.totalHits += 1
stats.totalPrefixHits += 1
lock.unlock()
// Dequantize if necessary before returning to caller
let cacheToReturn = Self.dequantizeCache(entry.kvCache)
return CacheLease(
entryId: match.entryId,
kvCache: cacheToReturn,
matchedTokenCount: match.realTokenCount,
isHit: true
)
}
if walkedFullKey,
let superLease = findSupersequenceMatchLocked(
below: node,
queryRealTokenCount: realTokenCount,
modelId: modelId,
now: now
) {
lock.unlock()
return superLease
}
if !walkedFullKey,
realTokenCount > 0,
let lcpLease = findLCPMatchLocked(
below: node,
sharedRealTokenCount: realTokenCount,
queryRealTokenCount: queryRealTokenCount,
modelId: modelId,
now: now
) {
lock.unlock()
return lcpLease
}
stats.totalMisses += 1
lock.unlock()
return CacheLease(entryId: UUID(), kvCache: nil, matchedTokenCount: 0, isHit: false)
}
func store(
entryId: UUID,
kvCache: [KVCache],
cacheKey: [Int],
modelId: String
) {
lock.lock()
let now = nowProvider()
pruneExpiredLocked(now: now)
let normalizedCache = Self.normalizeCacheForStorage(kvCache)
let bytesBeforeQuantization = estimateBytesProvider(normalizedCache)
let cacheToStore: [KVCache]
if quantizationConfig.enabled && cacheKey.filter({ $0 >= 0 }).count >= quantizationConfig.minTokens {
cacheToStore = Self.quantizeCache(normalizedCache, config: quantizationConfig)
} else {
cacheToStore = normalizedCache
}
let isQuantized = Self.cacheContainsQuantizedLayers(cacheToStore)
let estimatedBytes = estimateBytesProvider(cacheToStore)
let bytesSaved = bytesBeforeQuantization - estimatedBytes
// Update quantization stats if applicable
if isQuantized && bytesSaved > 0 {
stats.totalQuantizationBytesSaved += bytesSaved
}
var node = root
for key in cacheKey {
if node.children[key] == nil {
node.children[key] = TrieNode()
}
node = node.children[key]!
}
if let oldId = node.entryId,
let oldEntry = entries[oldId] {
removeEntryLocked(oldEntry, countAsEviction: false)
}
node.entryId = entryId
entries[entryId] = CacheEntry(
id: entryId,
modelId: modelId,
kvCache: cacheToStore,
tokenCount: cacheKey.filter { $0 >= 0 }.count,
cacheKey: cacheKey,
estimatedBytes: estimatedBytes,
createdAt: now,
lastAccessAt: now,
hitCount: 0,
isQuantized: isQuantized
)
currentMemoryBytes += estimatedBytes
enforceBudgetLocked()
lock.unlock()
}
func invalidateAll() {
lock.lock()
stats.totalEvictions += entries.count
entries.removeAll()
root = TrieNode()
currentMemoryBytes = 0
lock.unlock()
}
func reset() {
lock.lock()
root = TrieNode()
entries.removeAll()
currentMemoryBytes = 0
stats = Stats()
lock.unlock()
}
func snapshot() -> Snapshot {
lock.lock()
let now = nowProvider()
pruneExpiredLocked(now: now)
let orderedEntries = entries.values.sorted { lhs, rhs in
if lhs.lastAccessAt != rhs.lastAccessAt {
return lhs.lastAccessAt > rhs.lastAccessAt
}
return lhs.createdAt > rhs.createdAt
}
let hits = stats.totalHits
let misses = stats.totalMisses
let totalOps = hits + misses
let snapshot = Snapshot(
totalEntries: orderedEntries.count,
totalCachedTokens: orderedEntries.reduce(0) { $0 + $1.tokenCount },
estimatedBytes: currentMemoryBytes,
memoryBudgetBytes: maxMemoryBytes,
memoryUsagePercent: maxMemoryBytes > 0
? (Double(currentMemoryBytes) / Double(maxMemoryBytes)) * 100
: 0,
totalHits: hits,
totalMisses: misses,
totalEvictions: stats.totalEvictions,
hitRate: totalOps > 0 ? (Double(hits) / Double(totalOps)) * 100 : 0,
prefixHits: stats.totalPrefixHits,
supersequenceHits: stats.totalSupersequenceHits,
lcpHits: stats.totalLCPHits,
quantizationBytesSaved: stats.totalQuantizationBytesSaved,
quantizationEnabled: quantizationConfig.enabled,
entries: orderedEntries.map {
EntrySummary(
id: $0.id,
modelId: $0.modelId,
tokenCount: $0.tokenCount,
estimatedBytes: $0.estimatedBytes,
createdAt: $0.createdAt,
lastAccessAt: $0.lastAccessAt,
hitCount: $0.hitCount
)
}
)
lock.unlock()
return snapshot
}
func debugTrieNodeCount() -> Int {
lock.lock()
let count = countNodes(root)
lock.unlock()
return count
}
private func pruneExpiredLocked(now: Date) {
let expired = entries.values.filter {
now.timeIntervalSince($0.lastAccessAt) > idleTTL
}
for entry in expired {
removeEntryLocked(entry, countAsEviction: true)
}
}
private func enforceBudgetLocked() {
while currentMemoryBytes > maxMemoryBytes {
guard let victim = entries.values.min(by: evictionOrder) else {
break
}
removeEntryLocked(victim, countAsEviction: true)
}
}
private func removeEntryLocked(_ entry: CacheEntry, countAsEviction: Bool) {
guard entries[entry.id] != nil else { return }
var node = root
var path: [(parent: TrieNode, key: Int)] = []
for key in entry.cacheKey {
guard let child = node.children[key] else { break }
path.append((parent: node, key: key))
node = child
}
node.entryId = nil
for (parent, key) in path.reversed() {
guard let child = parent.children[key] else { continue }
if child.children.isEmpty && child.entryId == nil {
parent.children.removeValue(forKey: key)
} else {
break
}
}
currentMemoryBytes = max(0, currentMemoryBytes - entry.estimatedBytes)
entries.removeValue(forKey: entry.id)
if countAsEviction {
stats.totalEvictions += 1
}
}
private func evictionOrder(lhs: CacheEntry, rhs: CacheEntry) -> Bool {
if lhs.lastAccessAt != rhs.lastAccessAt {
return lhs.lastAccessAt < rhs.lastAccessAt
}
if lhs.hitCount != rhs.hitCount {
return lhs.hitCount < rhs.hitCount
}
return lhs.createdAt < rhs.createdAt
}
private func countNodes(_ node: TrieNode) -> Int {
1 + node.children.values.reduce(0) { $0 + countNodes($1) }
}
private func findSupersequenceMatchLocked(
below node: TrieNode,
queryRealTokenCount: Int,
modelId: String,
now: Date
) -> CacheLease? {
var queue: [TrieNode] = [node]
var bestEntry: CacheEntry?
while !queue.isEmpty {
let current = queue.removeFirst()
if let entryId = current.entryId,
let entry = entries[entryId],
entry.modelId == modelId,
entry.tokenCount > queryRealTokenCount,
entry.kvCache.allSatisfy({ $0.isTrimmable }) {
if bestEntry == nil || entry.tokenCount < bestEntry!.tokenCount {
bestEntry = entry
}
}
for child in current.children.values {
queue.append(child)
}
}
guard let entry = bestEntry,
let trimmedCache = Self.trimCacheByOffset(entry.kvCache, trimBy: entry.tokenCount - queryRealTokenCount)
else {
return nil
}
var updatedEntry = entry
updatedEntry.lastAccessAt = now
updatedEntry.hitCount += 1
entries[entry.id] = updatedEntry
removeEntryLocked(updatedEntry, countAsEviction: false)
stats.totalHits += 1
stats.totalSupersequenceHits += 1
// Dequantize if necessary before returning to caller
let cacheToReturn = Self.dequantizeCache(trimmedCache)
return CacheLease(
entryId: updatedEntry.id,
kvCache: cacheToReturn,
matchedTokenCount: queryRealTokenCount,
isHit: true
)
}
private func findLCPMatchLocked(
below node: TrieNode,
sharedRealTokenCount: Int,
queryRealTokenCount: Int,
modelId: String,
now: Date
) -> CacheLease? {
guard sharedRealTokenCount >= Self.minimumLCPMatchTokens(for: queryRealTokenCount) else {
return nil
}
var queue = Array(node.children.values)
var bestEntry: CacheEntry?
while !queue.isEmpty {
let current = queue.removeFirst()
if let entryId = current.entryId,
let entry = entries[entryId],
entry.modelId == modelId,
entry.tokenCount > sharedRealTokenCount,
entry.kvCache.allSatisfy({ $0.isTrimmable }) {
if bestEntry == nil || entry.tokenCount < bestEntry!.tokenCount {
bestEntry = entry
}
}
for child in current.children.values {
queue.append(child)
}
}
guard let entry = bestEntry,
let trimmedCache = Self.trimCacheByOffset(entry.kvCache, trimBy: entry.tokenCount - sharedRealTokenCount)
else {
return nil
}
var updatedEntry = entry
updatedEntry.lastAccessAt = now
updatedEntry.hitCount += 1
entries[entry.id] = updatedEntry
removeEntryLocked(updatedEntry, countAsEviction: false)
stats.totalHits += 1
stats.totalLCPHits += 1
// Dequantize if necessary before returning to caller
let cacheToReturn = Self.dequantizeCache(trimmedCache)
return CacheLease(
entryId: updatedEntry.id,
kvCache: cacheToReturn,
matchedTokenCount: sharedRealTokenCount,
isHit: true
)
}
private static func trimCacheByOffset(_ cache: [KVCache], trimBy: Int) -> [KVCache]? {
guard trimBy >= 0 else { return nil }
guard trimBy > 0 else { return cache }
for layer in cache {
guard layer.isTrimmable else { return nil }
let trimmed = layer.trim(trimBy)
guard trimmed == trimBy else { return nil }
}
return cache
}
private static func minimumLCPMatchTokens(for queryRealTokenCount: Int) -> Int {
guard queryRealTokenCount > 0 else { return .max }
return max(2, (queryRealTokenCount + 1) / 2)
}
private static func computeMemoryBudget() -> Int {
guard let device = MTLCreateSystemDefaultDevice() else {
return computeMemoryBudget(recommendedWorkingSetSize: nil)
}
return computeMemoryBudget(recommendedWorkingSetSize: Int(device.recommendedMaxWorkingSetSize))
}
static func computeMemoryBudget(recommendedWorkingSetSize: Int?) -> Int {
guard let recommendedWorkingSetSize else {
return 512 * 1024 * 1024
}
let budget = Int(Double(recommendedWorkingSetSize) * 0.20)
return max(256 * 1024 * 1024, min(budget, 8 * 1024 * 1024 * 1024))
}
private static func estimateBytes(_ kvCache: [KVCache]) -> Int {
var total = 0
for layer in kvCache {
for array in layer.state {
total += array.nbytes
}
}
return max(total, 1024)
}
// MARK: - Quantization Support
/// Quantize a KV cache for compact storage (Phase 6 feature).
/// Converts FP16 K/V tensors to a lower-bit representation.
/// Returns the quantized cache or the original cache if quantization is skipped/unsupported.
private static func quantizeCache(
_ cache: [KVCache],
config: QuantizationConfig
) -> [KVCache] {
guard config.enabled else { return cache }
return cache.map { layer in
if layer is QuantizedKVCache {
return layer
}
if let simpleLayer = layer as? KVCacheSimple {
let quantized = simpleLayer.toQuantized(
groupSize: config.groupSize,
bits: config.bits
)
MLX.eval(quantized.state)
return quantized
}
// Preserve non-standard cache types unchanged.
return layer
}
}
/// Dequantize a KV cache back to standard form before inference.
/// If the cache was not quantized, returns it unchanged.
private static func dequantizeCache(_ cache: [KVCache]) -> [KVCache] {
cache.map { layer in
if let quantizedLayer = layer as? QuantizedKVCache {
let unquantized = quantizedLayer.toUnquantized()
MLX.eval(unquantized.state)
return unquantized
}
return layer
}
}
private static func normalizeCacheForStorage(_ cache: [KVCache]) -> [KVCache] {
cache.map { layer in
if let quantizedLayer = layer as? QuantizedKVCache {
let compact = QuantizedKVCache(
groupSize: quantizedLayer.groupSize,
bits: quantizedLayer.bits,
mode: quantizedLayer.mode
)
compact.state = quantizedLayer.state
compact.offset = quantizedLayer.offset
MLX.eval(compact.state)
return compact
}
if let simpleLayer = layer as? KVCacheSimple {
let compact = KVCacheSimple()
compact.state = simpleLayer.state
MLX.eval(compact.state)
return compact
}
return layer
}
}
private static func cacheContainsQuantizedLayers(_ cache: [KVCache]) -> Bool {
cache.contains { $0 is QuantizedKVCache }
}
}

72
MLXServer/Utilities/Preferences.swift
View File

@@ -6,6 +6,7 @@ enum Preferences {
private static let jsonEncoder = JSONEncoder() private static let jsonEncoder = JSONEncoder()
private static let jsonDecoder = JSONDecoder() private static let jsonDecoder = JSONDecoder()
private static let legacyThinkingDefault = true
// MARK: - Last used model // MARK: - Last used model
@@ -79,12 +80,53 @@ enum Preferences {
// MARK: - Thinking mode // MARK: - Thinking mode
private static let enableThinkingKey = "enableThinking" private static let enableThinkingKey = "enableThinking"
private static let modelGenerationSettingsKey = "modelGenerationSettings"
/// Whether to enable thinking/reasoning mode for models that support it (e.g. Qwen3.5). /// Whether to enable thinking/reasoning mode for models that support it (e.g. Qwen3.5).
/// When disabled, the model skips internal reasoning and responds directly. /// When disabled, the model skips internal reasoning and responds directly.
static var enableThinking: Bool { static var enableThinking: Bool {
get { defaults.object(forKey: enableThinkingKey) == nil ? true : defaults.bool(forKey: enableThinkingKey) } get {
set { defaults.set(newValue, forKey: enableThinkingKey) } let modelId = defaultModelId ?? lastModelId ?? ModelConfig.default.id
if modelGenerationSettingsMap[modelId] != nil {
return generationSettings(forModelId: modelId).thinkingEnabled
}
return defaults.object(forKey: enableThinkingKey) == nil ? Self.legacyThinkingDefault : defaults.bool(forKey: enableThinkingKey)
}
set {
let modelId = defaultModelId ?? lastModelId ?? ModelConfig.default.id
var settings = generationSettings(forModelId: modelId)
settings.thinkingEnabled = newValue
setGenerationSettings(settings, forModelId: modelId)
defaults.set(newValue, forKey: enableThinkingKey)
}
}
static func generationSettings(forModelId modelId: String) -> GenerationSettings {
let legacyThinking = defaults.object(forKey: enableThinkingKey) == nil ? Self.legacyThinkingDefault : defaults.bool(forKey: enableThinkingKey)
return (modelGenerationSettingsMap[modelId] ?? GenerationSettings.modelDefault(for: modelId, legacyThinkingEnabled: legacyThinking)).normalized()
}
static func setGenerationSettings(_ settings: GenerationSettings, forModelId modelId: String) {
var map = modelGenerationSettingsMap
let normalized = settings.normalized()
map[modelId] = normalized
modelGenerationSettingsMap = map
defaults.set(normalized.thinkingEnabled, forKey: enableThinkingKey)
}
static func hasGenerationSettings(forModelId modelId: String) -> Bool {
modelGenerationSettingsMap[modelId] != nil
}
private static var modelGenerationSettingsMap: [String: GenerationSettings] {
get {
guard let data = defaults.data(forKey: modelGenerationSettingsKey) else { return [:] }
return (try? jsonDecoder.decode([String: GenerationSettings].self, from: data)) ?? [:]
}
set {
guard let data = try? jsonEncoder.encode(newValue) else { return }
defaults.set(data, forKey: modelGenerationSettingsKey)
}
} }
// MARK: - Idle unload // MARK: - Idle unload
@@ -98,4 +140,30 @@ enum Preferences {
} }
set { defaults.set(newValue, forKey: idleUnloadMinutesKey) } set { defaults.set(newValue, forKey: idleUnloadMinutesKey) }
} }
// MARK: - KV Cache Quantization
private static let kvQuantizationEnabledKey = "kvQuantizationEnabled"
private static let kvQuantizationBitsKey = "kvQuantizationBits"
/// Whether to quantize KV caches for compact storage (50% memory savings at 8-bit).
/// Default: false (disabled for maximum quality). Requires TokenPrefixCache Phase 6.
static var kvQuantizationEnabled: Bool {
get { defaults.object(forKey: kvQuantizationEnabledKey) == nil ? false : defaults.bool(forKey: kvQuantizationEnabledKey) }
set { defaults.set(newValue, forKey: kvQuantizationEnabledKey) }
}
/// Bit width for KV cache quantization. Standard: 8 (recommended). Range: 4-16.
/// Lower bits = more compression but potential quality loss. 8-bit is proven in production.
static var kvQuantizationBits: Int {
get {
let val = defaults.integer(forKey: kvQuantizationBitsKey)
return val > 0 ? val : 8
}
set {
// Clamp to valid range
let clamped = max(4, min(newValue, 16))
defaults.set(clamped, forKey: kvQuantizationBitsKey)
}
}
} }

114
MLXServer/ViewModels/ChatViewModel.swift
View File

@@ -28,8 +28,7 @@ final class ChatViewModel {
private var documentId = UUID() private var documentId = UUID()
private var documentCreatedAt = Date() private var documentCreatedAt = Date()
private var documentSystemPromptOverride: String? private var documentSystemPromptOverride: String?
private var documentThinkingOverride: Bool? private var documentGenerationSettingsOverride: GenerationSettings?
private var documentTemperature = 0.7
let modelManager: ModelManager let modelManager: ModelManager
let apiServer = APIServer() let apiServer = APIServer()
@@ -50,17 +49,58 @@ final class ChatViewModel {
hasUnsavedChanges ? "\(documentDisplayName) *" : documentDisplayName hasUnsavedChanges ? "\(documentDisplayName) *" : documentDisplayName
} }
var currentContextLength: Int {
modelManager.currentModel?.contextLength ?? 0
}
var estimatedPromptTokens: Int {
let draft = inputText.trimmingCharacters(in: .whitespacesAndNewlines)
var chatMessages = conversation.messages.compactMap(historyMessage(from:))
if !draft.isEmpty {
chatMessages.append(Chat.Message(role: .user, content: draft))
}
return PromptBuilder.estimatePromptTokens(
instructions: effectiveSystemPrompt,
chatMessages: chatMessages
)
}
var contextUsedTokens: Int {
if isGenerating && (promptTokens > 0 || generationTokens > 0) {
return promptTokens + generationTokens
}
return estimatedPromptTokens
}
var contextFillRatio: Double {
guard currentContextLength > 0 else { return 0 }
return min(max(Double(contextUsedTokens) / Double(currentContextLength), 0), 1)
}
/// Ensure a ChatSession exists for the current model. /// Ensure a ChatSession exists for the current model.
private func ensureSession() { private func ensureSession() {
guard let container = modelManager.modelContainer else { return } guard let container = modelManager.modelContainer else { return }
if chatSession == nil { if chatSession == nil {
let systemPrompt = effectiveSystemPrompt let systemPrompt = effectiveSystemPrompt
let generationSettings = effectiveGenerationSettings
// Pass enable_thinking to the Jinja chat template context. // Pass enable_thinking to the Jinja chat template context.
// Qwen3.5 and similar models use this to control reasoning mode. // Qwen3.5 and similar models use this to control reasoning mode.
let thinkingContext: [String: any Sendable]? = effectiveThinkingEnabled let thinkingContext: [String: any Sendable]? = generationSettings.thinkingEnabled
? nil ? nil
: ["enable_thinking": false] : ["enable_thinking": false]
let generateParameters = GenerateParameters(temperature: Float(documentTemperature)) let generateParameters = GenerateParameters(
maxTokens: generationSettings.maxTokens,
temperature: Float(generationSettings.temperature),
topP: Float(generationSettings.topP),
topK: generationSettings.topK,
minP: Float(generationSettings.minP),
repetitionPenalty: generationSettings.repetitionPenalty.map(Float.init),
repetitionContextSize: 128,
presencePenalty: generationSettings.presencePenalty.map(Float.init),
presenceContextSize: 128,
frequencyPenalty: generationSettings.frequencyPenalty.map(Float.init),
frequencyContextSize: 128
)
let history = conversation.messages.compactMap(historyMessage(from:)) let history = conversation.messages.compactMap(historyMessage(from:))
if history.isEmpty { if history.isEmpty {
chatSession = ChatSession( chatSession = ChatSession(
@@ -96,8 +136,17 @@ final class ChatViewModel {
return parts.joined(separator: "\n\n") return parts.joined(separator: "\n\n")
} }
private var effectiveThinkingEnabled: Bool { private var effectiveGenerationSettings: GenerationSettings {
documentThinkingOverride ?? Preferences.enableThinking if let documentGenerationSettingsOverride {
return documentGenerationSettingsOverride
}
let modelId = activeScene?.resolvedModel?.id
?? modelManager.currentModel?.id
?? Preferences.defaultModelId
?? ModelConfig.default.id
return Preferences.generationSettings(forModelId: modelId)
.applying(activeScene?.generationOverrides ?? .none)
} }
func send() { func send() {
@@ -181,15 +230,18 @@ final class ChatViewModel {
} }
func stop() { func stop() {
generationTask?.cancel() _ = cancelActiveGeneration()
generationTask = nil }
isGenerating = false
if let last = conversation.messages.indices.last, func prepareForTermination() async {
conversation.messages[last].isStreaming { autosaveToSandbox()
conversation.finalizeMessage(at: last)
markDirtyIfNeeded() let activeGeneration = cancelActiveGeneration()
} await apiServer.shutdown()
await activeGeneration?.value
resetSession()
modelManager.unloadModel()
} }
func attachImage(_ image: NSImage) { func attachImage(_ image: NSImage) {
@@ -266,8 +318,7 @@ final class ChatViewModel {
documentId = package.manifest.documentId documentId = package.manifest.documentId
documentCreatedAt = package.manifest.createdAt documentCreatedAt = package.manifest.createdAt
documentSystemPromptOverride = package.manifest.settings.systemPrompt documentSystemPromptOverride = package.manifest.settings.systemPrompt
documentThinkingOverride = package.manifest.settings.thinkingEnabled documentGenerationSettingsOverride = package.manifest.settings.generationSettings
documentTemperature = package.manifest.settings.temperature
resetSession() resetSession()
lastSavedSnapshotHash = try snapshotHash() lastSavedSnapshotHash = try snapshotHash()
hasUnsavedChanges = false hasUnsavedChanges = false
@@ -313,8 +364,7 @@ final class ChatViewModel {
documentId = UUID() documentId = UUID()
documentCreatedAt = Date() documentCreatedAt = Date()
documentSystemPromptOverride = nil documentSystemPromptOverride = nil
documentThinkingOverride = nil documentGenerationSettingsOverride = nil
documentTemperature = 0.7
} }
private func restoreMessage( private func restoreMessage(
@@ -395,11 +445,7 @@ final class ChatViewModel {
updatedAt: updatedAt, updatedAt: updatedAt,
appVersion: Bundle.main.object(forInfoDictionaryKey: "CFBundleShortVersionString") as? String ?? "1.0.0", appVersion: Bundle.main.object(forInfoDictionaryKey: "CFBundleShortVersionString") as? String ?? "1.0.0",
model: currentStoredModelInfo, model: currentStoredModelInfo,
settings: .init( settings: .init(systemPrompt: effectiveSystemPrompt, generationSettings: effectiveGenerationSettings),
systemPrompt: effectiveSystemPrompt,
thinkingEnabled: effectiveThinkingEnabled,
temperature: documentTemperature
),
messages: messages, messages: messages,
uiState: .init( uiState: .init(
draftInput: inputText, draftInput: inputText,
@@ -440,11 +486,7 @@ final class ChatViewModel {
documentId: documentId, documentId: documentId,
createdAt: documentCreatedAt, createdAt: documentCreatedAt,
model: currentStoredModelInfo, model: currentStoredModelInfo,
settings: .init( settings: .init(systemPrompt: effectiveSystemPrompt, generationSettings: effectiveGenerationSettings),
systemPrompt: effectiveSystemPrompt,
thinkingEnabled: effectiveThinkingEnabled,
temperature: documentTemperature
),
messages: makeManifest(updatedAt: documentCreatedAt).messages, messages: makeManifest(updatedAt: documentCreatedAt).messages,
uiState: .init(draftInput: inputText, scrollAnchorMessageId: conversation.messages.last?.id) uiState: .init(draftInput: inputText, scrollAnchorMessageId: conversation.messages.last?.id)
) )
@@ -564,4 +606,20 @@ final class ChatViewModel {
func stopAPIServer() { func stopAPIServer() {
apiServer.stop() apiServer.stop()
} }
@discardableResult
private func cancelActiveGeneration() -> Task<Void, Never>? {
let activeGeneration = generationTask
activeGeneration?.cancel()
generationTask = nil
isGenerating = false
if let last = conversation.messages.indices.last,
conversation.messages[last].isStreaming {
conversation.finalizeMessage(at: last)
markDirtyIfNeeded()
}
return activeGeneration
}
} }

31
MLXServer/ViewModels/ModelManager.swift
View File

@@ -34,6 +34,22 @@ final class ModelManager {
private var idleTimer: Timer? private var idleTimer: Timer?
private(set) var lastUsed: Date? private(set) var lastUsed: Date?
private var latestLoadRequestID = UUID()
private func clearLoadedState() {
idleTimer?.invalidate()
idleTimer = nil
lastUsed = nil
modelContainer = nil
currentModel = nil
isLoading = false
isDownloading = false
downloadProgress = 0
loadingModelName = ""
downloadFilesTotal = 0
downloadFilesCompleted = 0
downloadSpeed = 0
}
/// Load a model, unloading the current one first. /// Load a model, unloading the current one first.
/// Prefers the local snapshot from ~/.cache/huggingface/hub/ (shared with the Python server). /// Prefers the local snapshot from ~/.cache/huggingface/hub/ (shared with the Python server).
@@ -43,7 +59,10 @@ final class ModelManager {
return // already loaded return // already loaded
} }
unloadModel() let requestID = UUID()
latestLoadRequestID = requestID
clearLoadedState()
MLX.GPU.clearCache()
isLoading = true isLoading = true
downloadProgress = 0 downloadProgress = 0
loadingModelName = config.displayName loadingModelName = config.displayName
@@ -94,15 +113,18 @@ final class ModelManager {
) )
} }
guard latestLoadRequestID == requestID else { return }
self.isDownloading = false self.isDownloading = false
self.modelContainer = container self.modelContainer = container
self.currentModel = config self.currentModel = config
touchActivity() touchActivity()
} catch { } catch {
guard latestLoadRequestID == requestID else { return }
self.isDownloading = false self.isDownloading = false
self.errorMessage = "Failed to load model: \(error.localizedDescription)" self.errorMessage = "Failed to load model: \(error.localizedDescription)"
} }
guard latestLoadRequestID == requestID else { return }
isLoading = false isLoading = false
} }
@@ -115,11 +137,8 @@ final class ModelManager {
/// Unload the current model and free GPU memory. /// Unload the current model and free GPU memory.
func unloadModel() { func unloadModel() {
idleTimer?.invalidate() latestLoadRequestID = UUID()
idleTimer = nil clearLoadedState()
lastUsed = nil
modelContainer = nil
currentModel = nil
MLX.GPU.clearCache() MLX.GPU.clearCache()
} }

3
MLXServer/ViewModels/SceneStore.swift
View File

@@ -16,7 +16,8 @@ final class SceneStore {
name: scene.displayName, name: scene.displayName,
modelId: scene.modelId, modelId: scene.modelId,
systemPrompt: scene.systemPrompt, systemPrompt: scene.systemPrompt,
starterPrompt: scene.starterPrompt starterPrompt: scene.starterPrompt,
generationOverrides: scene.generationOverrides
) )
} else { } else {
nextScene = .empty nextScene = .empty

255
MLXServer/Views/GenerationSettingsEditor.swift Normal file
View File

@@ -0,0 +1,255 @@
import SwiftUI
struct GenerationDefaultsEditor: View {
@Binding var settings: GenerationSettings
var body: some View {
Toggle("Enable thinking mode", isOn: $settings.thinkingEnabled)
DecimalSettingRow(title: "Temperature", value: $settings.temperature)
DecimalSettingRow(title: "Top P", value: $settings.topP)
IntegerSettingRow(title: "Top K", value: $settings.topK)
DecimalSettingRow(title: "Min P", value: $settings.minP)
IntegerSettingRow(title: "Max tokens", value: $settings.maxTokens)
OptionalDecimalSettingRow(title: "Repetition penalty", value: $settings.repetitionPenalty, fallbackValue: 1.0)
OptionalDecimalSettingRow(title: "Presence penalty", value: $settings.presencePenalty, fallbackValue: 0.0)
OptionalDecimalSettingRow(title: "Frequency penalty", value: $settings.frequencyPenalty, fallbackValue: 0.0)
}
}
struct GenerationOverridesEditor: View {
@Binding var overrides: GenerationSettingsOverride
let inheritedSettings: GenerationSettings
let inheritedSource: String
var body: some View {
Picker("Thinking mode", selection: $overrides.thinkingEnabled) {
Text("Inherited (\(inheritedSettings.thinkingEnabled ? "Enabled" : "Disabled"))").tag(Optional<Bool>.none)
Text("Enabled").tag(Optional(true))
Text("Disabled").tag(Optional(false))
}
OptionalDecimalSettingRow(title: "Temperature", value: $overrides.temperature, fallbackValue: inheritedSettings.temperature, inherited: true)
OptionalDecimalSettingRow(title: "Top P", value: $overrides.topP, fallbackValue: inheritedSettings.topP, inherited: true)
OptionalIntegerSettingRow(title: "Top K", value: $overrides.topK, fallbackValue: inheritedSettings.topK, inherited: true)
OptionalDecimalSettingRow(title: "Min P", value: $overrides.minP, fallbackValue: inheritedSettings.minP, inherited: true)
OptionalIntegerSettingRow(title: "Max tokens", value: $overrides.maxTokens, fallbackValue: inheritedSettings.maxTokens, inherited: true)
OptionalDecimalSettingRow(title: "Repetition penalty", value: $overrides.repetitionPenalty, fallbackValue: inheritedSettings.repetitionPenalty ?? 0, inherited: true)
OptionalDecimalSettingRow(title: "Presence penalty", value: $overrides.presencePenalty, fallbackValue: inheritedSettings.presencePenalty ?? 0, inherited: true)
OptionalDecimalSettingRow(title: "Frequency penalty", value: $overrides.frequencyPenalty, fallbackValue: inheritedSettings.frequencyPenalty ?? 0, inherited: true)
Text("Unset fields inherit from \(inheritedSource). The values shown are the effective starting values for this scene.")
.font(.caption)
.foregroundStyle(.secondary)
}
}
private struct DecimalSettingRow: View {
let title: String
@Binding var value: Double
@State private var text: String
init(title: String, value: Binding<Double>) {
self.title = title
self._value = value
self._text = State(initialValue: NumericFieldFormatting.doubleString(value.wrappedValue))
}
var body: some View {
HStack {
Text(title)
Spacer()
TextField("", text: $text)
.multilineTextAlignment(.trailing)
.frame(width: 90)
.onChange(of: text) {
if let parsed = NumericFieldFormatting.parseDouble(text) {
value = parsed
}
}
.onChange(of: value) {
let formatted = NumericFieldFormatting.doubleString(value)
if text != formatted {
text = formatted
}
}
}
}
}
private struct IntegerSettingRow: View {
let title: String
@Binding var value: Int
@State private var text: String
init(title: String, value: Binding<Int>) {
self.title = title
self._value = value
self._text = State(initialValue: NumericFieldFormatting.intString(value.wrappedValue))
}
var body: some View {
HStack {
Text(title)
Spacer()
TextField("", text: $text)
.multilineTextAlignment(.trailing)
.frame(width: 90)
.onChange(of: text) {
if let parsed = NumericFieldFormatting.parseInt(text) {
value = parsed
}
}
.onChange(of: value) {
let formatted = NumericFieldFormatting.intString(value)
if text != formatted {
text = formatted
}
}
}
}
}
private struct OptionalDecimalSettingRow: View {
let title: String
@Binding var value: Double?
let fallbackValue: Double
var inherited = false
@State private var text: String
init(title: String, value: Binding<Double?>, fallbackValue: Double, inherited: Bool = false) {
self.title = title
self._value = value
self.fallbackValue = fallbackValue
self.inherited = inherited
self._text = State(initialValue: NumericFieldFormatting.doubleString(value.wrappedValue ?? fallbackValue))
}
var body: some View {
HStack {
Text(title)
Spacer()
TextField("", text: $text)
.multilineTextAlignment(.trailing)
.frame(width: 90)
.onChange(of: text) {
if let parsed = NumericFieldFormatting.parseDouble(text) {
value = parsed
}
}
.onChange(of: value) {
syncText()
}
.onChange(of: fallbackValue) {
if value == nil {
syncText()
}
}
if inherited && value == nil {
Text("Inherited")
.font(.caption)
.foregroundStyle(.secondary)
}
Button(value == nil ? "Override" : "Clear") {
if value == nil {
value = fallbackValue
} else {
value = nil
}
syncText()
}
.buttonStyle(.link)
}
}
private func syncText() {
let formatted = NumericFieldFormatting.doubleString(value ?? fallbackValue)
if text != formatted {
text = formatted
}
}
}
private struct OptionalIntegerSettingRow: View {
let title: String
@Binding var value: Int?
let fallbackValue: Int
var inherited = false
@State private var text: String
init(title: String, value: Binding<Int?>, fallbackValue: Int, inherited: Bool = false) {
self.title = title
self._value = value
self.fallbackValue = fallbackValue
self.inherited = inherited
self._text = State(initialValue: NumericFieldFormatting.intString(value.wrappedValue ?? fallbackValue))
}
var body: some View {
HStack {
Text(title)
Spacer()
TextField("", text: $text)
.multilineTextAlignment(.trailing)
.frame(width: 90)
.onChange(of: text) {
if let parsed = NumericFieldFormatting.parseInt(text) {
value = parsed
}
}
.onChange(of: value) {
syncText()
}
.onChange(of: fallbackValue) {
if value == nil {
syncText()
}
}
if inherited && value == nil {
Text("Inherited")
.font(.caption)
.foregroundStyle(.secondary)
}
Button(value == nil ? "Override" : "Clear") {
if value == nil {
value = fallbackValue
} else {
value = nil
}
syncText()
}
.buttonStyle(.link)
}
}
private func syncText() {
let formatted = NumericFieldFormatting.intString(value ?? fallbackValue)
if text != formatted {
text = formatted
}
}
}
private enum NumericFieldFormatting {
static func parseDouble(_ text: String) -> Double? {
let trimmed = text.trimmingCharacters(in: .whitespacesAndNewlines)
guard !trimmed.isEmpty else { return nil }
return Double(trimmed.replacingOccurrences(of: ",", with: "."))
}
static func parseInt(_ text: String) -> Int? {
let trimmed = text.trimmingCharacters(in: .whitespacesAndNewlines)
guard !trimmed.isEmpty else { return nil }
return Int(trimmed)
}
static func doubleString(_ value: Double) -> String {
if value.rounded() == value {
return String(Int(value))
}
return String(value)
}
static func intString(_ value: Int) -> String {
String(value)
}
}

1063
MLXServer/Views/MonitorView.swift
View File

File diff suppressed because it is too large Load Diff

39
MLXServer/Views/SceneManagementView.swift
View File

@@ -246,6 +246,14 @@ private struct SceneEditorView: View {
.font(.caption) .font(.caption)
.foregroundStyle(.secondary) .foregroundStyle(.secondary)
} }
Section("Generation Overrides") {
GenerationOverridesEditor(
overrides: generationOverridesBinding,
inheritedSettings: inheritedGenerationSettings,
inheritedSource: inheritedGenerationSource
)
}
} }
.formStyle(.grouped) .formStyle(.grouped)
.navigationTitle(scene.displayName) .navigationTitle(scene.displayName)
@@ -272,4 +280,35 @@ private struct SceneEditorView: View {
} }
) )
} }
private var generationOverridesBinding: Binding<GenerationSettingsOverride> {
Binding(
get: { sceneStore.scene(id: scene.id)?.generationOverrides ?? scene.generationOverrides },
set: { newValue in
sceneStore.updateScene(id: scene.id) {
$0.generationOverrides = newValue
}
}
)
}
private var effectiveModelId: String {
sceneStore.scene(id: scene.id)?.modelId
?? scene.modelId
?? Preferences.defaultModelId
?? Preferences.lastModelId
?? ModelConfig.default.id
}
private var inheritedGenerationSettings: GenerationSettings {
Preferences.generationSettings(forModelId: effectiveModelId)
}
private var inheritedGenerationSource: String {
let modelName = ModelConfig.resolve(effectiveModelId)?.displayName ?? effectiveModelId
if Preferences.hasGenerationSettings(forModelId: effectiveModelId) {
return "saved \(modelName) defaults"
}
return "built-in \(modelName) defaults"
}
} }

75
MLXServer/Views/SettingsView.swift
View File

@@ -8,7 +8,22 @@ struct SettingsView: View {
@State private var apiAutoStart: Bool = Preferences.apiAutoStart @State private var apiAutoStart: Bool = Preferences.apiAutoStart
@State private var idleUnloadMinutes: String = String(Preferences.idleUnloadMinutes) @State private var idleUnloadMinutes: String = String(Preferences.idleUnloadMinutes)
@State private var defaultModelId: String = Preferences.defaultModelId ?? ModelConfig.default.id @State private var defaultModelId: String = Preferences.defaultModelId ?? ModelConfig.default.id
@State private var enableThinking: Bool = Preferences.enableThinking @State private var generationDefaultsModelId: String = Preferences.defaultModelId ?? ModelConfig.default.id
@State private var kvQuantizationEnabled: Bool = Preferences.kvQuantizationEnabled
@State private var kvQuantizationBits: Int = Preferences.kvQuantizationBits
private var kvQuantizationConfig: TokenPrefixCache.QuantizationConfig {
guard kvQuantizationEnabled else {
return .default
}
return .init(
enabled: true,
bits: kvQuantizationBits,
groupSize: 64,
minTokens: 256
)
}
var body: some View { var body: some View {
Form { Form {
@@ -27,13 +42,16 @@ struct SettingsView: View {
.foregroundStyle(.secondary) .foregroundStyle(.secondary)
} }
Section("Generation") { Section("Generation Defaults") {
Toggle("Enable thinking mode", isOn: $enableThinking) Picker("Defaults for model", selection: $generationDefaultsModelId) {
.onChange(of: enableThinking) { ForEach(ModelConfig.availableModels) { model in
Preferences.enableThinking = enableThinking Text(model.displayName).tag(model.id)
} }
}
Text("When enabled, models like Qwen3.5 reason internally before responding. Produces better answers but slower. Takes effect on the next conversation.") GenerationDefaultsEditor(settings: generationDefaultsBinding)
Text("These are the per-model defaults used by chat sessions and by the API server whenever a request omits a generation parameter. Lower temperature and stronger repetition penalties are usually better for technical work; higher temperature is usually better for improvisation and roleplay.")
.font(.caption) .font(.caption)
.foregroundStyle(.secondary) .foregroundStyle(.secondary)
} }
@@ -107,8 +125,51 @@ struct SettingsView: View {
.font(.caption) .font(.caption)
.foregroundStyle(.secondary) .foregroundStyle(.secondary)
} }
Section("Cache Quantization") {
Toggle("Enable KV cache quantization", isOn: $kvQuantizationEnabled)
.onChange(of: kvQuantizationEnabled) {
Preferences.kvQuantizationEnabled = kvQuantizationEnabled
TokenPrefixCache.shared.setQuantizationConfig(kvQuantizationConfig)
}
if kvQuantizationEnabled {
HStack {
Text("Bit width")
Spacer()
Stepper(
value: $kvQuantizationBits,
in: 4...16,
step: 1
) {
Text("\(kvQuantizationBits)-bit")
}
.onChange(of: kvQuantizationBits) {
Preferences.kvQuantizationBits = kvQuantizationBits
TokenPrefixCache.shared.setQuantizationConfig(kvQuantizationConfig)
}
}
}
if kvQuantizationEnabled {
Text("Quantizes KV caches to \(kvQuantizationBits)-bit for \(kvQuantizationBits == 8 ? "~50%" : "~\((16 - kvQuantizationBits) * 6)%") memory savings. Lower bits = more compression but may impact response quality. 8-bit is recommended.")
.font(.caption)
.foregroundStyle(.secondary)
} else {
Text("When enabled, KV caches are quantized for compact storage, reducing memory usage on long conversations. Disabled by default for maximum quality.")
.font(.caption)
.foregroundStyle(.secondary)
}
}
} }
.formStyle(.grouped) .formStyle(.grouped)
.frame(width: 450, height: 550) .frame(width: 450, height: 650)
}
private var generationDefaultsBinding: Binding<GenerationSettings> {
Binding(
get: { Preferences.generationSettings(forModelId: generationDefaultsModelId) },
set: { Preferences.setGenerationSettings($0, forModelId: generationDefaultsModelId) }
)
} }
} }

43
MLXServer/Views/StatusBarView.swift
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@@ -31,6 +31,10 @@ struct StatusBarView: View {
.font(.caption) .font(.caption)
.foregroundStyle(.secondary) .foregroundStyle(.secondary)
if let model = modelManager.currentModel, model.contextLength > 0 {
contextFillView(totalContext: model.contextLength)
}
Spacer() Spacer()
// GPU memory // GPU memory
@@ -78,4 +82,43 @@ struct StatusBarView: View {
.padding(.vertical, 4) .padding(.vertical, 4)
.background(.bar) .background(.bar)
} }
@ViewBuilder
private func contextFillView(totalContext: Int) -> some View {
let usedTokens = viewModel.contextUsedTokens
let ratio = viewModel.contextFillRatio
let percent = Int((ratio * 100).rounded())
HStack(spacing: 6) {
Capsule()
.fill(.quaternary)
.frame(width: 48, height: 6)
.overlay(alignment: .leading) {
Capsule()
.fill(contextFillColor(for: ratio))
.frame(width: max(4, 48 * ratio), height: 6)
}
Text("Ctx \(percent)%")
.font(.caption.monospacedDigit())
.foregroundStyle(.secondary)
}
.help("Approximate context usage: \(formatTokenCount(usedTokens)) of \(formatTokenCount(totalContext)) tokens")
}
private func contextFillColor(for ratio: Double) -> Color {
if ratio >= 0.9 { return .red }
if ratio >= 0.7 { return .yellow }
return .blue
}
private func formatTokenCount(_ count: Int) -> String {
if count >= 1_000_000 {
return String(format: "%.1fM", Double(count) / 1_000_000)
}
if count >= 1_000 {
return String(format: "%.1fk", Double(count) / 1_000)
}
return "\(count)"
}
} }

44
MLXServerTests/Server/APIServerResponseResolutionTests.swift Normal file
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@@ -0,0 +1,44 @@
import MLXLMCommon
import XCTest
@testable import MLX_Server
final class APIServerResponseResolutionTests: XCTestCase {
@MainActor
func testResolveAssistantResponseUsesFrameworkToolCalls() throws {
let frameworkToolCalls = [
ToolCall(function: ToolCall.Function(name: "weather", arguments: ["city": "Berlin"]))
]
let resolved = APIServer.resolveAssistantResponse(
fullText: "I will call the tool.",
frameworkToolCalls: frameworkToolCalls,
tools: [mockWeatherTool]
)
XCTAssertEqual(resolved.finishReason, "tool_calls")
XCTAssertEqual(resolved.content, "I will call the tool.")
let toolCall = try XCTUnwrap(resolved.toolCalls?.first)
XCTAssertEqual(toolCall.function.name, "weather")
XCTAssertEqual(toolCall.function.arguments, #"{"city":"Berlin"}"#)
}
private var mockWeatherTool: APIToolDefinition {
APIToolDefinition(
type: "function",
function: APIFunctionDefinition(
name: "weather",
description: "Look up weather for a city.",
parameters: [
"type": AnyCodable("object"),
"properties": AnyCodable([
"city": [
"type": "string",
"description": "City name"
]
]),
"required": AnyCodable(["city"])
]
)
)
}
}

1836
MLXServerTests/Server/APIServerRewriteTests.swift Normal file
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18
MLXServerTests/Server/CancellationTokenTests.swift Normal file
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@@ -0,0 +1,18 @@
import XCTest
@testable import MLX_Server
final class CancellationTokenTests: XCTestCase {
func testStartsNotCancelled() {
let token = CancellationToken()
XCTAssertFalse(token.isCancelled)
}
func testCancelSetsFlag() {
let token = CancellationToken()
token.cancel()
XCTAssertTrue(token.isCancelled)
}
}

46
MLXServerTests/Server/ChatViewModelTests.swift Normal file
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@@ -0,0 +1,46 @@
import XCTest
@testable import MLX_Server
@MainActor
final class ChatViewModelTests: XCTestCase {
func testQwenChatViewModelSendProducesAssistantReply() async throws {
let modelManager = ModelManager()
let config = try XCTUnwrap(ModelConfig.resolve("qwen3.5-0.8b"))
await modelManager.loadModel(config)
defer { modelManager.unloadModel() }
XCTAssertTrue(modelManager.isReady)
let viewModel = ChatViewModel(modelManager: modelManager)
viewModel.inputText = "Say hello in one word."
viewModel.send()
XCTAssertTrue(viewModel.isGenerating)
try await waitUntil(timeoutSeconds: 15) {
!viewModel.isGenerating
}
XCTAssertEqual(viewModel.conversation.messages.count, 2)
XCTAssertEqual(viewModel.conversation.messages[0].role, .user)
XCTAssertEqual(viewModel.conversation.messages[0].content, "Say hello in one word.")
XCTAssertEqual(viewModel.conversation.messages[1].role, .assistant)
XCTAssertFalse(viewModel.conversation.messages[1].sessionContent.isEmpty)
XCTAssertGreaterThan(viewModel.promptTokens, 0)
}
private func waitUntil(
timeoutSeconds: TimeInterval,
intervalNanoseconds: UInt64 = 100_000_000,
condition: @escaping @MainActor () -> Bool
) async throws {
let deadline = Date().addingTimeInterval(timeoutSeconds)
while Date() < deadline {
if condition() {
return
}
try await Task.sleep(nanoseconds: intervalNanoseconds)
}
XCTFail("Condition not met before timeout")
}
}

80
MLXServerTests/Server/GenerationSettingsTests.swift Normal file
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@@ -0,0 +1,80 @@
import XCTest
@testable import MLX_Server
final class GenerationSettingsTests: XCTestCase {
func testSceneOverridesApplyWithoutDiscardingModelDefaults() {
let base = GenerationSettings(
temperature: 0.2,
topP: 0.9,
topK: 12,
minP: 0.05,
maxTokens: 2048,
repetitionPenalty: 1.08,
presencePenalty: 0.3,
frequencyPenalty: 0.1,
thinkingEnabled: true
)
let overrides = GenerationSettingsOverride(
temperature: 0.8,
repetitionPenalty: 1.2,
thinkingEnabled: false
)
let resolved = base.applying(overrides)
XCTAssertEqual(resolved.temperature, 0.8)
XCTAssertEqual(resolved.repetitionPenalty, 1.2)
XCTAssertEqual(resolved.topP, 0.9)
XCTAssertEqual(resolved.topK, 12)
XCTAssertEqual(resolved.maxTokens, 2048)
XCTAssertEqual(resolved.presencePenalty, 0.3)
XCTAssertFalse(resolved.thinkingEnabled)
}
func testPreferencesStoreGenerationDefaultsPerModel() {
let gemmaId = "gemma"
let qwenId = "qwen3.5-0.8b"
let originalGemma = Preferences.generationSettings(forModelId: gemmaId)
let originalQwen = Preferences.generationSettings(forModelId: qwenId)
defer {
Preferences.setGenerationSettings(originalGemma, forModelId: gemmaId)
Preferences.setGenerationSettings(originalQwen, forModelId: qwenId)
}
Preferences.setGenerationSettings(
GenerationSettings(temperature: 0.15, topP: 0.85, maxTokens: 1024, repetitionPenalty: 1.1, thinkingEnabled: false),
forModelId: gemmaId
)
Preferences.setGenerationSettings(
GenerationSettings(temperature: 0.95, topP: 1.0, maxTokens: 8192, repetitionPenalty: nil, thinkingEnabled: true),
forModelId: qwenId
)
let gemma = Preferences.generationSettings(forModelId: gemmaId)
let qwen = Preferences.generationSettings(forModelId: qwenId)
XCTAssertEqual(gemma.temperature, 0.15)
XCTAssertEqual(gemma.topP, 0.85)
XCTAssertEqual(gemma.maxTokens, 1024)
XCTAssertEqual(gemma.repetitionPenalty, 1.1)
XCTAssertFalse(gemma.thinkingEnabled)
XCTAssertEqual(qwen.temperature, 0.95)
XCTAssertEqual(qwen.maxTokens, 8192)
XCTAssertNil(qwen.repetitionPenalty)
XCTAssertTrue(qwen.thinkingEnabled)
}
func testModelFallbackDefaultsComeFromModelDefinitions() {
let gemma = GenerationSettings.modelDefault(for: "gemma")
let qwen = GenerationSettings.modelDefault(for: "qwen")
let stheno = GenerationSettings.modelDefault(for: "stheno")
XCTAssertEqual(gemma, .technicalDefault)
XCTAssertEqual(qwen, .technicalDefault)
XCTAssertEqual(stheno, .roleplayDefault)
XCTAssertNotEqual(gemma, stheno)
}
}

39
MLXServerTests/Server/ImageDecoderTests.swift Normal file
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@@ -0,0 +1,39 @@
import MLXLMCommon
import XCTest
@testable import MLX_Server
final class ImageDecoderTests: XCTestCase {
func testDecodeDataURI() {
let image = ImageDecoder.decode(TestImageFixtures.primaryDataURI)
XCTAssertNotNil(image)
XCTAssertGreaterThanOrEqual(image?.estimatedBytes ?? 0, 4)
}
func testDecodePlainBase64() {
let image = ImageDecoder.decode(TestImageFixtures.primaryPNGBase64)
XCTAssertNotNil(image)
XCTAssertGreaterThanOrEqual(image?.estimatedBytes ?? 0, 4)
}
func testDecodeJPEGDataURI() {
let image = ImageDecoder.decode(TestImageFixtures.primaryJPEGDataURI)
XCTAssertNotNil(image)
XCTAssertGreaterThanOrEqual(image?.estimatedBytes ?? 0, 64 * 64 * 4)
}
func testDecodeLarge4KDataURI() throws {
let image = try XCTUnwrap(ImageDecoder.decode(TestImageFixtures.largeDataURI))
XCTAssertGreaterThanOrEqual(image.estimatedBytes, 4_096 * 4_096 * 4)
if case .ciImage(let ciImage) = image.image {
XCTAssertEqual(Int(ciImage.extent.width), 4_096)
XCTAssertEqual(Int(ciImage.extent.height), 4_096)
} else {
XCTFail("Expected CIImage-backed decoded image")
}
}
}

46
MLXServerTests/Server/LiveCountersTests.swift Normal file
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@@ -0,0 +1,46 @@
import Foundation
import XCTest
@testable import MLX_Server
final class LiveCountersTests: XCTestCase {
override func tearDown() {
LiveCounters.shared.reset()
super.tearDown()
}
func testTracksRequestMetricsAndDeduplicatesDisconnects() {
let requestId = "req-1"
LiveCounters.shared.reset()
LiveCounters.shared.requestStarted(requestId: requestId, contextLength: 8_192)
LiveCounters.shared.requestPhaseChanged(requestId: requestId, phase: .prefilling)
LiveCounters.shared.recordPrefillReuse(requestId: requestId, matchedPromptTokens: 40, promptTokenCount: 64)
LiveCounters.shared.visionProcessingCompleted(requestId: requestId, duration: 0.25)
Thread.sleep(forTimeInterval: 0.01)
LiveCounters.shared.prefillCompleted(requestId: requestId, promptTokens: 64)
Thread.sleep(forTimeInterval: 0.01)
LiveCounters.shared.firstTokenGenerated(requestId: requestId)
LiveCounters.shared.tokenGenerated(tokensPerSecond: 12.5, totalGenerated: 3)
LiveCounters.shared.disconnectDetected(requestId: requestId)
LiveCounters.shared.disconnectDetected(requestId: requestId)
let inFlight = LiveCounters.shared.snapshot()
XCTAssertEqual(inFlight.cacheMatchDepth, 40)
XCTAssertEqual(inFlight.currentCacheMatchedPromptTokens, 40)
XCTAssertEqual(inFlight.currentCacheRebuiltPromptTokens, 24)
XCTAssertEqual(inFlight.visionEncoderTime, 0.25, accuracy: 0.0001)
XCTAssertGreaterThan(inFlight.prefillTokensPerSecond, 0)
XCTAssertGreaterThan(inFlight.timeToFirstToken, 0)
XCTAssertEqual(inFlight.totalDisconnects, 1)
LiveCounters.shared.requestCompleted(requestId: requestId, generationTokens: 3)
let completed = LiveCounters.shared.snapshot()
XCTAssertEqual(completed.totalPromptTokens, 64)
XCTAssertEqual(completed.totalGenerationTokens, 3)
XCTAssertEqual(completed.totalVisionEncoderDuration, 0.25, accuracy: 0.0001)
XCTAssertEqual(completed.totalDisconnects, 1)
}
}

691
MLXServerTests/Server/ModelBackedInferenceValidationTests.swift Normal file
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@@ -0,0 +1,691 @@
import Foundation
import Hub
import MLXLMCommon
import MLXVLM
import XCTest
@testable import MLX_Server
private struct GemmaPreprocessorConfig: Decodable {
let do_resize: Bool
let size: GemmaPreprocessorSize
}
private struct GemmaPreprocessorSize: Decodable {
let height: Int
let width: Int
}
final class ModelBackedInferenceValidationTests: XCTestCase {
func testPromptBuilderTokenizationMatchesLegacyShapingOnLocalGemma() async throws {
let container = try await localGemmaContainer()
let engine = InferenceEngine(container: container)
let request = APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(role: "system", content: .text("You are concise."), name: nil, tool_calls: nil, tool_call_id: nil),
APIChatMessage(
role: "user",
content: .parts([
APIContentPart(type: "text", text: "What is in this image?", image_url: nil),
APIContentPart(type: "image_url", text: nil, image_url: APIImageURL(url: TestImageFixtures.primaryDataURI, detail: nil))
]),
name: nil,
tool_calls: nil,
tool_call_id: nil
)
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
)
let prepared = PromptBuilder.build(from: request, modelId: "mlx-community/gemma-3-4b-it-4bit", thinkingEnabled: false)
let legacy = legacyBuild(from: request, modelId: "mlx-community/gemma-3-4b-it-4bit", thinkingEnabled: false)
let preparedInference = try await engine.prepare(prepared.userInput)
let legacyInference = try await engine.prepare(legacy.userInput)
XCTAssertEqual(preparedInference.tokens, legacyInference.tokens)
}
func testInferenceEngineMatchesChatSessionOnLocalGemma() async throws {
let container = try await localGemmaContainer()
let engine = InferenceEngine(container: container)
let parameters = GenerateParameters(maxTokens: 1, temperature: 0)
let request = APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(role: "user", content: .text("Say hello in one word."), name: nil, tool_calls: nil, tool_call_id: nil)
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
)
let prepared = PromptBuilder.build(from: request, modelId: "mlx-community/gemma-3-4b-it-4bit", thinkingEnabled: true)
let preparedInference = try await engine.prepare(prepared.userInput)
let handle = try await engine.stream(
InferenceEngine.InferenceRequest(
input: preparedInference.lmInput,
tokens: preparedInference.tokens,
parameters: parameters,
cachedKV: nil,
cachedTokenCount: 0
),
cancellation: CancellationToken()
)
let engineResult = await collectEngineOutput(handle.stream)
let session = ChatSession(container, generateParameters: parameters)
let sessionResult = try await collectSessionOutput(
session.streamDetails(to: "Say hello in one word.", images: [], videos: [])
)
XCTAssertEqual(engineResult.text, sessionResult.text)
XCTAssertEqual(engineResult.promptTokenCount, sessionResult.promptTokenCount)
}
func testVisionCacheKeyChangesWhenImageChangesButTokensStayTheSame() async throws {
let container = try await localGemmaContainer()
let engine = InferenceEngine(container: container)
let first = PromptBuilder.build(
from: visionRequest(dataURI: TestImageFixtures.primaryDataURI),
modelId: "mlx-community/gemma-3-4b-it-4bit",
thinkingEnabled: false
)
let second = PromptBuilder.build(
from: visionRequest(dataURI: TestImageFixtures.alternateDataURI),
modelId: "mlx-community/gemma-3-4b-it-4bit",
thinkingEnabled: false
)
let firstPrepared = try await engine.prepare(first.userInput, imageFingerprints: first.imageFingerprints)
let secondPrepared = try await engine.prepare(second.userInput, imageFingerprints: second.imageFingerprints)
XCTAssertEqual(firstPrepared.tokens, secondPrepared.tokens)
XCTAssertNotEqual(firstPrepared.cacheKey, secondPrepared.cacheKey)
}
func testStoredLiveGemmaVisionCacheReusesSameImagePrompt() async throws {
let container = try await localGemmaContainer()
let engine = InferenceEngine(container: container)
let prompt = PromptBuilder.build(
from: visionRequest(dataURI: TestImageFixtures.primaryDataURI),
modelId: "mlx-community/gemma-3-4b-it-4bit",
thinkingEnabled: false
)
let prepared = try await engine.prepare(prompt.userInput, imageFingerprints: prompt.imageFingerprints)
let handle = try await engine.stream(
InferenceEngine.InferenceRequest(
input: prepared.lmInput,
tokens: prepared.tokens,
parameters: GenerateParameters(maxTokens: 2, temperature: 0),
cachedKV: nil,
cachedTokenCount: 0
),
cancellation: CancellationToken()
)
_ = await collectEngineOutput(handle.stream)
trimCacheToPrompt(handle.workingCache, promptTokenCount: prepared.tokens.count)
let cache = TokenPrefixCache(memoryBudgetBytes: 1_000_000_000, estimateBytesProvider: { _ in 1_024 })
cache.store(entryId: UUID(), kvCache: handle.workingCache, cacheKey: prepared.cacheKey, modelId: "gemma")
let lease = cache.lookup(cacheKey: prepared.cacheKey, modelId: "gemma")
XCTAssertTrue(lease.isHit)
XCTAssertEqual(lease.matchedTokenCount, prepared.tokens.count)
}
func testLarge4KImageUsesGemmaResizeConfigAndPreparesSuccessfully() async throws {
let container = try await localGemmaContainer()
let engine = InferenceEngine(container: container)
let preprocessorURL = try XCTUnwrap(
LocalModelResolver.resolve(repoId: "mlx-community/gemma-3-4b-it-4bit")?
.appendingPathComponent("preprocessor_config.json"),
"Local Gemma preprocessor config is unavailable"
)
let preprocessorData = try Data(contentsOf: preprocessorURL)
let preprocessor = try JSONDecoder().decode(GemmaPreprocessorConfig.self, from: preprocessorData)
let decoded = try XCTUnwrap(ImageDecoder.decode(TestImageFixtures.largeDataURI))
let userInput = UserInput(
prompt: .chat([
Chat.Message(role: .user, content: "What is in this image?", images: [decoded.image])
]),
images: [decoded.image],
videos: [],
tools: nil,
additionalContext: ["enable_thinking": false]
)
let prepared = try await engine.prepare(userInput)
XCTAssertTrue(preprocessor.do_resize)
XCTAssertEqual(preprocessor.size.height, preprocessor.size.width)
XCTAssertLessThan(preprocessor.size.height, 4_096)
XCTAssertFalse(prepared.tokens.isEmpty)
}
func testTokenPrefixCacheFindsLCPHitForSameSystemDifferentUserOnLocalGemmaTokens() async throws {
let container = try await localGemmaContainer()
let engine = InferenceEngine(container: container)
let first = PromptBuilder.build(
from: APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(role: "system", content: .text("You are terse and literal."), name: nil, tool_calls: nil, tool_call_id: nil),
APIChatMessage(role: "user", content: .text("Respond with one word for cat."), name: nil, tool_calls: nil, tool_call_id: nil),
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
),
modelId: "mlx-community/gemma-3-4b-it-4bit",
thinkingEnabled: true
)
let second = PromptBuilder.build(
from: APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(role: "system", content: .text("You are terse and literal."), name: nil, tool_calls: nil, tool_call_id: nil),
APIChatMessage(role: "user", content: .text("Respond with one word for dog."), name: nil, tool_calls: nil, tool_call_id: nil),
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
),
modelId: "mlx-community/gemma-3-4b-it-4bit",
thinkingEnabled: true
)
let firstPrepared = try await engine.prepare(first.userInput)
let secondPrepared = try await engine.prepare(second.userInput)
let cache = TokenPrefixCache(memoryBudgetBytes: 1_000_000, estimateBytesProvider: { _ in 1_024 })
cache.store(entryId: UUID(), kvCache: [], cacheKey: firstPrepared.tokens, modelId: "gemma")
let lease = cache.lookup(cacheKey: secondPrepared.tokens, modelId: "gemma")
XCTAssertTrue(lease.isHit)
XCTAssertGreaterThan(lease.matchedTokenCount, 0)
XCTAssertLessThan(lease.matchedTokenCount, firstPrepared.tokens.count)
}
func testStoredLiveGemmaCacheSupportsSameSystemDifferentUserLCPReuse() async throws {
let container = try await localGemmaContainer()
let engine = InferenceEngine(container: container)
let first = PromptBuilder.build(
from: APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(role: "system", content: .text("You are terse and literal."), name: nil, tool_calls: nil, tool_call_id: nil),
APIChatMessage(role: "user", content: .text("Respond with one word for cat."), name: nil, tool_calls: nil, tool_call_id: nil),
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
),
modelId: "mlx-community/gemma-3-4b-it-4bit",
thinkingEnabled: true
)
let second = PromptBuilder.build(
from: APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(role: "system", content: .text("You are terse and literal."), name: nil, tool_calls: nil, tool_call_id: nil),
APIChatMessage(role: "user", content: .text("Respond with one word for dog."), name: nil, tool_calls: nil, tool_call_id: nil),
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
),
modelId: "mlx-community/gemma-3-4b-it-4bit",
thinkingEnabled: true
)
let firstPrepared = try await engine.prepare(first.userInput)
let secondPrepared = try await engine.prepare(second.userInput)
let handle = try await engine.stream(
InferenceEngine.InferenceRequest(
input: firstPrepared.lmInput,
tokens: firstPrepared.tokens,
parameters: GenerateParameters(maxTokens: 2, temperature: 0),
cachedKV: nil,
cachedTokenCount: 0
),
cancellation: CancellationToken()
)
_ = await collectEngineOutput(handle.stream)
trimCacheToPrompt(handle.workingCache, promptTokenCount: firstPrepared.tokens.count)
let cache = TokenPrefixCache(memoryBudgetBytes: 1_000_000_000, estimateBytesProvider: { _ in 1_024 })
cache.store(entryId: UUID(), kvCache: handle.workingCache, cacheKey: firstPrepared.tokens, modelId: "gemma")
let lease = cache.lookup(cacheKey: secondPrepared.tokens, modelId: "gemma")
XCTAssertTrue(lease.isHit)
XCTAssertGreaterThan(lease.matchedTokenCount, 0)
XCTAssertLessThan(lease.matchedTokenCount, firstPrepared.tokens.count)
}
func testStoredLiveGemmaCacheSupportsSupersequenceReuseForShorterPrefix() async throws {
let container = try await localGemmaContainer()
let engine = InferenceEngine(container: container)
let prompt = PromptBuilder.build(
from: APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(role: "system", content: .text("You are terse and literal."), name: nil, tool_calls: nil, tool_call_id: nil),
APIChatMessage(role: "user", content: .text("Respond with one word for cat, then one word for dog."), name: nil, tool_calls: nil, tool_call_id: nil),
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
),
modelId: "mlx-community/gemma-3-4b-it-4bit",
thinkingEnabled: true
)
let prepared = try await engine.prepare(prompt.userInput)
XCTAssertGreaterThan(prepared.tokens.count, 16)
let handle = try await engine.stream(
InferenceEngine.InferenceRequest(
input: prepared.lmInput,
tokens: prepared.tokens,
parameters: GenerateParameters(maxTokens: 2, temperature: 0),
cachedKV: nil,
cachedTokenCount: 0
),
cancellation: CancellationToken()
)
_ = await collectEngineOutput(handle.stream)
trimCacheToPrompt(handle.workingCache, promptTokenCount: prepared.tokens.count)
let shorterTokenCount = prepared.tokens.count - 16
let shorterPrefix = Array(prepared.tokens.prefix(shorterTokenCount))
let cache = TokenPrefixCache(memoryBudgetBytes: 1_000_000_000, estimateBytesProvider: { _ in 1_024 })
cache.store(entryId: UUID(), kvCache: handle.workingCache, cacheKey: prepared.tokens, modelId: "gemma")
let lease = cache.lookup(cacheKey: shorterPrefix, modelId: "gemma")
XCTAssertTrue(lease.isHit)
XCTAssertEqual(lease.matchedTokenCount, shorterTokenCount)
let leasedCache = try XCTUnwrap(lease.kvCache)
XCTAssertFalse(leasedCache.isEmpty)
for layer in leasedCache {
XCTAssertEqual(layer.offset, shorterTokenCount)
}
let snapshot = cache.snapshot()
XCTAssertEqual(snapshot.supersequenceHits, 1)
XCTAssertEqual(snapshot.lcpHits, 0)
XCTAssertEqual(snapshot.prefixHits, 0)
}
func testTokenPrefixCacheCanFalseHitDifferentSystemPromptsOnRawGemmaTokens() async throws {
let container = try await localGemmaContainer()
let engine = InferenceEngine(container: container)
let first = PromptBuilder.build(
from: APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(role: "system", content: .text("System Alpha Unique Tokens"), name: nil, tool_calls: nil, tool_call_id: nil),
APIChatMessage(role: "user", content: .text("Answer in one word: tree."), name: nil, tool_calls: nil, tool_call_id: nil),
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
),
modelId: "mlx-community/gemma-3-4b-it-4bit",
thinkingEnabled: true
)
let second = PromptBuilder.build(
from: APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(role: "system", content: .text("Completely Different Beta Markers"), name: nil, tool_calls: nil, tool_call_id: nil),
APIChatMessage(role: "user", content: .text("Answer in one word: tree."), name: nil, tool_calls: nil, tool_call_id: nil),
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
),
modelId: "mlx-community/gemma-3-4b-it-4bit",
thinkingEnabled: true
)
let firstPrepared = try await engine.prepare(first.userInput)
let secondPrepared = try await engine.prepare(second.userInput)
let cache = TokenPrefixCache(memoryBudgetBytes: 1_000_000, estimateBytesProvider: { _ in 1_024 })
cache.store(entryId: UUID(), kvCache: [], cacheKey: firstPrepared.tokens, modelId: "gemma")
let lease = cache.lookup(cacheKey: secondPrepared.tokens, modelId: "gemma")
XCTAssertFalse(lease.isHit)
}
private func localGemmaContainer() async throws -> ModelContainer {
try await LocalGemmaFixture.shared.container()
}
private func trimCacheToPrompt(_ cache: [KVCache], promptTokenCount: Int) {
for layer in cache {
let excess = layer.offset - promptTokenCount
if excess > 0 {
XCTAssertTrue(layer.isTrimmable)
XCTAssertEqual(layer.trim(excess), excess)
}
}
}
private func legacyBuild(
from request: APIChatCompletionRequest,
modelId: String,
thinkingEnabled: Bool
) -> PromptBuilder.PreparedPrompt {
var instructions = ""
for msg in request.messages where msg.role == "system" {
let text = msg.content?.textContent ?? ""
if !text.isEmpty {
if !instructions.isEmpty { instructions += "\n\n" }
instructions += text
}
}
if let tools = request.tools, !tools.isEmpty {
let toolSystemPrompt = ToolPromptBuilder.buildSystemPrompt(tools: tools, modelId: modelId)
if !instructions.isEmpty { instructions += "\n\n" }
instructions += toolSystemPrompt
}
let isQwen = modelId.lowercased().contains("qwen")
var chatMessages: [Chat.Message] = []
var messageSignatures: [UInt64] = []
var estimatedBytes = instructions.utf8.count
var containsImages = false
for msg in request.messages where msg.role != "system" {
let role: Chat.Message.Role = switch msg.role {
case "assistant": .assistant
case "tool": .user
default: .user
}
var text = msg.content?.textContent ?? ""
if msg.role == "tool", !isQwen {
text = "```tool_output\n\(text)\n```"
}
if msg.role == "assistant", let toolCalls = msg.tool_calls, !toolCalls.isEmpty {
let formattedCalls = isQwen
? ToolPromptBuilder.formatQwenToolCalls(toolCalls)
: ToolPromptBuilder.formatGemmaToolCalls(toolCalls)
text = (text.isEmpty ? "" : text + "\n") + formattedCalls
}
let imageURLs = msg.content?.imageURLs ?? []
var messageImages: [UserInput.Image] = []
var messageImageBytes = 0
for urlString in imageURLs {
if let decoded = ImageDecoder.decode(urlString) {
messageImages.append(decoded.image)
messageImageBytes += decoded.estimatedBytes
}
}
containsImages = containsImages || !messageImages.isEmpty
chatMessages.append(Chat.Message(role: role, content: text, images: messageImages))
messageSignatures.append(messageSignature(role: role, content: text, imageURLs: imageURLs))
estimatedBytes += text.utf8.count + messageImageBytes
}
let additionalContext: [String: any Sendable]? = thinkingEnabled
? nil
: ["enable_thinking": false]
let allImages = chatMessages.flatMap(\.images)
let allMessages = (instructions.isEmpty ? [] : [Chat.Message(role: .system, content: instructions)]) + chatMessages
let userInput = UserInput(
prompt: .chat(allMessages),
images: allImages,
videos: [],
tools: nil,
additionalContext: additionalContext
)
return PromptBuilder.PreparedPrompt(
instructions: instructions,
chatMessages: chatMessages,
messageSignatures: messageSignatures,
imageFingerprints: imageURLsFingerprintOrder(from: request),
estimatedBytes: estimatedBytes,
estimatedPromptTokens: (instructions.count + chatMessages.reduce(0) { $0 + $1.content.count }) * 10 / 35,
containsImages: containsImages,
additionalContext: additionalContext,
userInput: userInput
)
}
private func visionRequest(dataURI: String) -> APIChatCompletionRequest {
APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(
role: "user",
content: .parts([
APIContentPart(type: "text", text: "What is in this image?", image_url: nil),
APIContentPart(type: "image_url", text: nil, image_url: APIImageURL(url: dataURI, detail: nil))
]),
name: nil,
tool_calls: nil,
tool_call_id: nil
)
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
)
}
private func imageURLsFingerprintOrder(from request: APIChatCompletionRequest) -> [UInt64] {
request.messages
.filter { $0.role != "system" }
.flatMap { $0.content?.imageURLs ?? [] }
.reduce(into: [UInt64]()) { fingerprints, imageURL in
var hash: UInt64 = 14_695_981_039_346_656_037
for byte in imageURL.utf8 {
hash ^= UInt64(byte)
hash &*= 1_099_511_628_211
}
fingerprints.append(hash)
}
}
private func messageSignature(role: Chat.Message.Role, content: String, imageURLs: [String]) -> UInt64 {
var hash: UInt64 = 14_695_981_039_346_656_037
func mix(_ text: String) {
for byte in text.utf8 {
hash ^= UInt64(byte)
hash &*= 1_099_511_628_211
}
}
switch role {
case .assistant:
mix("assistant")
case .system:
mix("system")
case .user:
mix("user")
@unknown default:
mix("unknown")
}
mix("|")
mix(content)
for imageURL in imageURLs {
mix("|")
mix(imageURL)
}
return hash
}
private func collectEngineOutput(_ stream: AsyncStream<Generation>) async -> GenerationResult {
var text = ""
var promptTokenCount = 0
for await generation in stream {
switch generation {
case .chunk(let chunk):
text += chunk
case .info(let info):
promptTokenCount = info.promptTokenCount
case .toolCall:
break
}
}
return GenerationResult(text: text, promptTokenCount: promptTokenCount)
}
private func collectSessionOutput(_ stream: AsyncThrowingStream<Generation, any Error>) async throws -> GenerationResult {
var text = ""
var promptTokenCount = 0
for try await generation in stream {
switch generation {
case .chunk(let chunk):
text += chunk
case .info(let info):
promptTokenCount = info.promptTokenCount
case .toolCall:
break
}
}
return GenerationResult(text: text, promptTokenCount: promptTokenCount)
}
}
private struct GenerationResult {
let text: String
let promptTokenCount: Int
}
private actor LocalGemmaFixture {
static let shared = LocalGemmaFixture()
private var task: Task<ModelContainer, Error>?
func container() async throws -> ModelContainer {
if let task {
return try await task.value
}
guard let config = ModelConfig.resolve("gemma") else {
throw XCTSkip("Gemma model config is unavailable")
}
guard let localDir = LocalModelResolver.resolve(repoId: config.repoId) else {
throw XCTSkip("Local gemma cache is unavailable")
}
let loadTask = Task<ModelContainer, Error> {
let cachesDir = FileManager.default.urls(for: .cachesDirectory, in: .userDomainMask).first
let hub = HubApi(downloadBase: cachesDir, cache: nil)
return try await VLMModelFactory.shared.loadContainer(
hub: hub,
configuration: ModelConfiguration(directory: localDir),
progressHandler: { _ in }
)
}
task = loadTask
do {
return try await loadTask.value
} catch {
task = nil
throw error
}
}
}

251
MLXServerTests/Server/ModelBackedQuantizationTests.swift Normal file
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import Foundation
import Hub
import MLX
import MLXLMCommon
import MLXVLM
import XCTest
@testable import MLX_Server
final class ModelBackedQuantizationTests: XCTestCase {
func testQuantizedLookupRoundTripPreservesRealModelCache() async throws {
let container = try await localGemmaContainer()
let engine = InferenceEngine(container: container)
let input = quantizationPrompt()
let prepared = try await engine.prepare(input)
let workingCache = try await generatePromptCache(
engine: engine,
prepared: prepared,
maxTokens: 1
)
let cache = TokenPrefixCache(
memoryBudgetBytes: 1_000_000_000,
quantizationConfig: .init(enabled: true, bits: 8, groupSize: 64, minTokens: 1)
)
cache.store(
entryId: UUID(),
kvCache: workingCache,
cacheKey: prepared.tokens,
modelId: "gemma"
)
let lease = cache.lookup(cacheKey: prepared.tokens, modelId: "gemma")
let roundTripped = try XCTUnwrap(lease.kvCache)
XCTAssertTrue(lease.isHit)
XCTAssertFalse(roundTripped.isEmpty)
XCTAssertFalse(roundTripped.contains { $0 is QuantizedKVCache })
XCTAssertEqual(workingCache.count, roundTripped.count)
for (original, returned) in zip(workingCache, roundTripped) {
XCTAssertEqual(original.offset, returned.offset)
XCTAssertEqual(original.state.count, returned.state.count)
for (lhs, rhs) in zip(original.state, returned.state) {
XCTAssertEqual(lhs.shape, rhs.shape)
}
}
}
func testQuantizedCacheHitProducesUsableDeterministicResponseAndAdvancesCacheLikeUnquantizedHit() async throws {
let container = try await localGemmaContainer()
let engine = InferenceEngine(container: container)
let input = quantizationPrompt()
let prepared = try await engine.prepare(input)
let promptCache = try await generatePromptCache(
engine: engine,
prepared: prepared,
maxTokens: 1
)
let unquantizedCache = TokenPrefixCache(
memoryBudgetBytes: 1_000_000_000,
quantizationConfig: .default
)
let quantizedCache = TokenPrefixCache(
memoryBudgetBytes: 1_000_000_000,
quantizationConfig: .init(enabled: true, bits: 8, groupSize: 64, minTokens: 1)
)
unquantizedCache.store(
entryId: UUID(),
kvCache: promptCache,
cacheKey: prepared.tokens,
modelId: "gemma"
)
quantizedCache.store(
entryId: UUID(),
kvCache: promptCache,
cacheKey: prepared.tokens,
modelId: "gemma"
)
let unquantizedLease = unquantizedCache.lookup(cacheKey: prepared.tokens, modelId: "gemma")
let quantizedLease = quantizedCache.lookup(cacheKey: prepared.tokens, modelId: "gemma")
XCTAssertTrue(unquantizedLease.isHit)
XCTAssertTrue(quantizedLease.isHit)
XCTAssertEqual(unquantizedLease.matchedTokenCount, prepared.tokens.count)
XCTAssertEqual(quantizedLease.matchedTokenCount, prepared.tokens.count)
let parameters = GenerateParameters(maxTokens: 4, temperature: 0)
let unquantizedHandle = try await engine.stream(
InferenceEngine.InferenceRequest(
input: prepared.lmInput,
tokens: prepared.tokens,
parameters: parameters,
cachedKV: unquantizedLease.kvCache,
cachedTokenCount: unquantizedLease.matchedTokenCount
),
cancellation: CancellationToken()
)
let unquantizedText = await collectText(unquantizedHandle.stream)
XCTAssertFalse(unquantizedText.isEmpty)
let quantizedHandle = try await engine.stream(
InferenceEngine.InferenceRequest(
input: prepared.lmInput,
tokens: prepared.tokens,
parameters: parameters,
cachedKV: quantizedLease.kvCache,
cachedTokenCount: quantizedLease.matchedTokenCount
),
cancellation: CancellationToken()
)
let quantizedText = await collectText(quantizedHandle.stream)
XCTAssertFalse(quantizedText.isEmpty)
XCTAssertEqual(unquantizedHandle.workingCache.count, quantizedHandle.workingCache.count)
for (lhs, rhs) in zip(unquantizedHandle.workingCache, quantizedHandle.workingCache) {
XCTAssertLessThanOrEqual(abs(lhs.offset - rhs.offset), 1)
XCTAssertEqual(lhs.state.count, rhs.state.count)
for (lhsState, rhsState) in zip(lhs.state, rhs.state) {
XCTAssertEqual(lhsState.shape.count, rhsState.shape.count)
if lhsState.shape.count == 4 {
XCTAssertEqual(lhsState.shape[0], rhsState.shape[0])
XCTAssertEqual(lhsState.shape[1], rhsState.shape[1])
XCTAssertLessThanOrEqual(abs(lhsState.shape[2] - rhsState.shape[2]), 1)
XCTAssertEqual(lhsState.shape[3], rhsState.shape[3])
} else {
XCTAssertEqual(lhsState.shape, rhsState.shape)
}
}
}
}
func testPreferencesIntegrationWithQuantization() throws {
Preferences.kvQuantizationEnabled = true
Preferences.kvQuantizationBits = 8
XCTAssertTrue(Preferences.kvQuantizationEnabled)
XCTAssertEqual(Preferences.kvQuantizationBits, 8)
Preferences.kvQuantizationBits = 2
XCTAssertGreaterThanOrEqual(Preferences.kvQuantizationBits, 4)
Preferences.kvQuantizationBits = 32
XCTAssertLessThanOrEqual(Preferences.kvQuantizationBits, 16)
Preferences.kvQuantizationEnabled = false
Preferences.kvQuantizationBits = 8
}
private func quantizationPrompt() -> UserInput {
UserInput(
prompt: .chat([
Chat.Message(role: .system, content: "You are terse and deterministic."),
Chat.Message(role: .user, content: String(repeating: "cache reuse test ", count: 48))
]),
images: [],
videos: [],
tools: nil
)
}
private func generatePromptCache(
engine: InferenceEngine,
prepared: InferenceEngine.PreparedInference,
maxTokens: Int
) async throws -> [KVCache] {
let handle = try await engine.stream(
InferenceEngine.InferenceRequest(
input: prepared.lmInput,
tokens: prepared.tokens,
parameters: GenerateParameters(maxTokens: maxTokens, temperature: 0),
cachedKV: nil,
cachedTokenCount: 0
),
cancellation: CancellationToken()
)
_ = await collectText(handle.stream)
trimCacheToPrompt(handle.workingCache, promptTokenCount: prepared.tokens.count)
return handle.workingCache
}
private func collectText(_ stream: AsyncStream<Generation>) async -> String {
var text = ""
for await generation in stream {
if case .chunk(let chunk) = generation {
text += chunk
}
}
return text
}
private func trimCacheToPrompt(_ cache: [KVCache], promptTokenCount: Int) {
for layer in cache {
let excess = layer.offset - promptTokenCount
if excess > 0 {
XCTAssertTrue(layer.isTrimmable)
XCTAssertEqual(layer.trim(excess), excess)
}
}
}
private func localGemmaContainer() async throws -> ModelContainer {
try await LocalGemmaFixture.shared.container()
}
}
// MARK: - LocalGemmaFixture
private actor LocalGemmaFixture {
static let shared = LocalGemmaFixture()
private var task: Task<ModelContainer, Error>?
func container() async throws -> ModelContainer {
if let task {
return try await task.value
}
guard let config = ModelConfig.resolve("gemma") else {
throw XCTSkip("Gemma model config is unavailable")
}
guard let localDir = LocalModelResolver.resolve(repoId: config.repoId) else {
throw XCTSkip("Local gemma cache is unavailable")
}
let loadTask = Task<ModelContainer, Error> {
let cachesDir = FileManager.default.urls(for: .cachesDirectory, in: .userDomainMask).first
let hub = HubApi(downloadBase: cachesDir, cache: nil)
return try await VLMModelFactory.shared.loadContainer(
hub: hub,
configuration: ModelConfiguration(directory: localDir),
progressHandler: { _ in }
)
}
task = loadTask
do {
return try await loadTask.value
} catch {
task = nil
throw error
}
}
}

376
MLXServerTests/Server/PromptBuilderTests.swift Normal file
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import XCTest
import MLXLMCommon
@testable import MLX_Server
final class PromptBuilderTests: XCTestCase {
func testBuildMatchesLegacyAPIServerShapingForGemma() {
let toolCall = APIToolCall(
id: "call_weather",
function: APIFunctionCall(name: "weather", arguments: "{\"city\":\"Berlin\"}")
)
let request = APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(role: "system", content: .text("System 1"), name: nil, tool_calls: nil, tool_call_id: nil),
APIChatMessage(role: "system", content: .text("System 2"), name: nil, tool_calls: nil, tool_call_id: nil),
APIChatMessage(role: "assistant", content: .text("Let me check"), name: nil, tool_calls: [toolCall], tool_call_id: nil),
APIChatMessage(
role: "tool",
content: .parts([
APIContentPart(type: "text", text: "{\"temp\":19}", image_url: nil),
APIContentPart(type: "image_url", text: nil, image_url: APIImageURL(url: TestImageFixtures.primaryDataURI, detail: nil))
]),
name: nil,
tool_calls: nil,
tool_call_id: "call_weather"
),
APIChatMessage(role: "user", content: .text("Thanks"), name: nil, tool_calls: nil, tool_call_id: nil)
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: [
APIToolDefinition(
type: "function",
function: APIFunctionDefinition(
name: "weather",
description: "Lookup weather",
parameters: ["type": AnyCodable("object")]
)
)
],
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
)
let prepared = PromptBuilder.build(from: request, modelId: "mlx-community/gemma-3-4b-it-4bit", thinkingEnabled: false)
let legacy = legacyBuild(from: request, modelId: "mlx-community/gemma-3-4b-it-4bit", thinkingEnabled: false)
XCTAssertEqual(prepared.instructions, legacy.instructions)
XCTAssertEqual(prepared.chatMessages.map { $0.role.roleLabel }, legacy.chatMessages.map { $0.role.roleLabel })
XCTAssertEqual(prepared.chatMessages.map(\.content), legacy.chatMessages.map(\.content))
XCTAssertEqual(prepared.chatMessages.map { $0.images.count }, legacy.chatMessages.map { $0.images.count })
XCTAssertEqual(prepared.messageSignatures, legacy.messageSignatures)
XCTAssertEqual(prepared.estimatedBytes, legacy.estimatedBytes)
XCTAssertEqual(prepared.estimatedPromptTokens, legacy.estimatedPromptTokens)
XCTAssertEqual(prepared.containsImages, legacy.containsImages)
XCTAssertEqual(prepared.additionalContext?["enable_thinking"] as? Bool, legacy.additionalContext?["enable_thinking"] as? Bool)
}
func testEstimatePromptTokensMatchesSharedCharacterHeuristic() {
let messages = [
Chat.Message(role: .user, content: "1234567890"),
Chat.Message(role: .assistant, content: "abcdefghij")
]
let estimated = PromptBuilder.estimatePromptTokens(
instructions: "system12345",
chatMessages: messages
)
XCTAssertEqual(estimated, 8)
}
func testBuildAggregatesInstructionsAndMessages() {
let request = APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(role: "system", content: .text("Base system"), name: nil, tool_calls: nil, tool_call_id: nil),
APIChatMessage(role: "system", content: .text("Extra system"), name: nil, tool_calls: nil, tool_call_id: nil),
APIChatMessage(role: "user", content: .text("Hello"), name: nil, tool_calls: nil, tool_call_id: nil)
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
)
let prepared = PromptBuilder.build(from: request, modelId: "mlx-community/gemma-3-4b-it-4bit", thinkingEnabled: false)
XCTAssertEqual(prepared.instructions, "Base system\n\nExtra system")
XCTAssertEqual(prepared.chatMessages.count, 1)
XCTAssertEqual(prepared.chatMessages[0].content, "Hello")
XCTAssertEqual(prepared.messageSignatures.count, 1)
XCTAssertFalse(prepared.containsImages)
XCTAssertNotNil(prepared.additionalContext)
XCTAssertGreaterThan(prepared.estimatedPromptTokens, 0)
}
func testBuildFormatsAssistantToolCallsForQwen() {
let toolCall = APIToolCall(
id: "call_1",
function: APIFunctionCall(name: "weather", arguments: "{\"city\":\"Berlin\"}")
)
let request = APIChatCompletionRequest(
model: "qwen",
messages: [
APIChatMessage(role: "assistant", content: .text("Let me check."), name: nil, tool_calls: [toolCall], tool_call_id: nil)
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
)
let prepared = PromptBuilder.build(from: request, modelId: "mlx-community/Qwen3.5-0.8B-4bit", thinkingEnabled: true)
XCTAssertEqual(prepared.chatMessages.count, 1)
XCTAssertTrue(prepared.chatMessages[0].content.contains("Let me check."))
XCTAssertTrue(prepared.chatMessages[0].content.contains("<tool_call>"))
XCTAssertNil(prepared.additionalContext)
}
func testBuildWrapsGemmaToolOutputsAndTracksImages() {
let request = APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(
role: "tool",
content: .parts([
APIContentPart(type: "text", text: "{\"ok\":true}", image_url: nil),
APIContentPart(type: "image_url", text: nil, image_url: APIImageURL(url: TestImageFixtures.primaryDataURI, detail: nil))
]),
name: nil,
tool_calls: nil,
tool_call_id: "call_1"
)
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
)
let prepared = PromptBuilder.build(from: request, modelId: "mlx-community/gemma-3-4b-it-4bit", thinkingEnabled: true)
XCTAssertTrue(prepared.chatMessages[0].content.contains("```tool_output"))
XCTAssertTrue(prepared.containsImages)
XCTAssertEqual(prepared.chatMessages[0].images.count, 1)
XCTAssertEqual(prepared.imageFingerprints.count, 1)
XCTAssertGreaterThan(prepared.estimatedBytes, prepared.chatMessages[0].content.utf8.count)
}
func testBuildHashesRawImageSourcesIntoStableFingerprints() {
let firstRequest = APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(
role: "user",
content: .parts([
APIContentPart(type: "text", text: "Describe this.", image_url: nil),
APIContentPart(type: "image_url", text: nil, image_url: APIImageURL(url: TestImageFixtures.primaryDataURI, detail: nil))
]),
name: nil,
tool_calls: nil,
tool_call_id: nil
)
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
)
let secondRequest = APIChatCompletionRequest(
model: "gemma",
messages: [
APIChatMessage(
role: "user",
content: .parts([
APIContentPart(type: "text", text: "Describe this.", image_url: nil),
APIContentPart(type: "image_url", text: nil, image_url: APIImageURL(url: TestImageFixtures.alternateDataURI, detail: nil))
]),
name: nil,
tool_calls: nil,
tool_call_id: nil
)
],
temperature: nil,
top_p: nil,
max_tokens: nil,
stream: nil,
stop: nil,
tools: nil,
tool_choice: nil,
frequency_penalty: nil,
presence_penalty: nil,
n: nil
)
let firstPrepared = PromptBuilder.build(from: firstRequest, modelId: "mlx-community/gemma-3-4b-it-4bit", thinkingEnabled: true)
let secondPrepared = PromptBuilder.build(from: secondRequest, modelId: "mlx-community/gemma-3-4b-it-4bit", thinkingEnabled: true)
XCTAssertEqual(firstPrepared.imageFingerprints.count, 1)
XCTAssertEqual(secondPrepared.imageFingerprints.count, 1)
XCTAssertNotEqual(firstPrepared.imageFingerprints, secondPrepared.imageFingerprints)
}
private func legacyBuild(
from request: APIChatCompletionRequest,
modelId: String,
thinkingEnabled: Bool
) -> PromptBuilder.PreparedPrompt {
var instructions = ""
for msg in request.messages where msg.role == "system" {
let text = msg.content?.textContent ?? ""
if !text.isEmpty {
if !instructions.isEmpty { instructions += "\n\n" }
instructions += text
}
}
if let tools = request.tools, !tools.isEmpty {
let toolSystemPrompt = ToolPromptBuilder.buildSystemPrompt(tools: tools, modelId: modelId)
if !instructions.isEmpty { instructions += "\n\n" }
instructions += toolSystemPrompt
}
let isQwen = modelId.lowercased().contains("qwen")
var chatMessages: [Chat.Message] = []
var messageSignatures: [UInt64] = []
var estimatedBytes = instructions.utf8.count
var containsImages = false
for msg in request.messages where msg.role != "system" {
let role: Chat.Message.Role = switch msg.role {
case "assistant": .assistant
case "tool": .user
default: .user
}
var text = msg.content?.textContent ?? ""
if msg.role == "tool", !isQwen {
text = "```tool_output\n\(text)\n```"
}
if msg.role == "assistant", let toolCalls = msg.tool_calls, !toolCalls.isEmpty {
let formattedCalls = isQwen
? ToolPromptBuilder.formatQwenToolCalls(toolCalls)
: ToolPromptBuilder.formatGemmaToolCalls(toolCalls)
text = (text.isEmpty ? "" : text + "\n") + formattedCalls
}
let imageURLs = msg.content?.imageURLs ?? []
var messageImages: [UserInput.Image] = []
var messageImageBytes = 0
for urlString in imageURLs {
if let decoded = ImageDecoder.decode(urlString) {
messageImages.append(decoded.image)
messageImageBytes += decoded.estimatedBytes
}
}
containsImages = containsImages || !messageImages.isEmpty
chatMessages.append(Chat.Message(role: role, content: text, images: messageImages))
messageSignatures.append(messageSignature(role: role, content: text, imageURLs: imageURLs))
estimatedBytes += text.utf8.count + messageImageBytes
}
let additionalContext: [String: any Sendable]? = thinkingEnabled
? nil
: ["enable_thinking": false]
let allImages = chatMessages.flatMap(\.images)
let userInput = UserInput(
prompt: .chat((instructions.isEmpty ? [] : [Chat.Message(role: .system, content: instructions)]) + chatMessages),
images: allImages,
videos: [],
tools: nil,
additionalContext: additionalContext
)
return PromptBuilder.PreparedPrompt(
instructions: instructions,
chatMessages: chatMessages,
messageSignatures: messageSignatures,
imageFingerprints: imageURLsFingerprintOrder(from: request),
estimatedBytes: estimatedBytes,
estimatedPromptTokens: (instructions.count + chatMessages.reduce(0) { $0 + $1.content.count }) * 10 / 35,
containsImages: containsImages,
additionalContext: additionalContext,
userInput: userInput
)
}
private func imageURLsFingerprintOrder(from request: APIChatCompletionRequest) -> [UInt64] {
request.messages
.filter { $0.role != "system" }
.flatMap { $0.content?.imageURLs ?? [] }
.reduce(into: [UInt64]()) { fingerprints, imageURL in
var hash: UInt64 = 14_695_981_039_346_656_037
for byte in imageURL.utf8 {
hash ^= UInt64(byte)
hash &*= 1_099_511_628_211
}
fingerprints.append(hash)
}
}
private func messageSignature(role: Chat.Message.Role, content: String, imageURLs: [String]) -> UInt64 {
var hash: UInt64 = 14_695_981_039_346_656_037
func mix(_ text: String) {
for byte in text.utf8 {
hash ^= UInt64(byte)
hash &*= 1_099_511_628_211
}
}
switch role {
case .assistant:
mix("assistant")
case .system:
mix("system")
case .user:
mix("user")
@unknown default:
mix("unknown")
}
mix("|")
mix(content)
for imageURL in imageURLs {
mix("|")
mix(imageURL)
}
return hash
}
}
private extension Chat.Message.Role {
var roleLabel: String {
switch self {
case .assistant: "assistant"
case .system: "system"
case .user: "user"
@unknown default: "unknown"
}
}
}

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import XCTest
@testable import MLX_Server
final class StreamingSSEEncoderTests: XCTestCase {
func testEncodeContentDeltaMatchesJSONEncoderOutput() throws {
let encoder = StreamingSSEEncoder(requestId: "chatcmpl-test", created: 1_234_567, modelName: "qwen\"model")
let text = "line 1\nline 2\t\"quoted\"\\slash"
let actual = encoder.encodeContentDelta(text)
let expected = try baselineData(
for: APIChatCompletionChunk(
id: "chatcmpl-test",
object: "chat.completion.chunk",
created: 1_234_567,
model: "qwen\"model",
choices: [
APIStreamChoice(
index: 0,
delta: APIDeltaMessage(role: nil, content: text, tool_calls: nil),
finish_reason: nil
)
],
usage: nil
)
)
XCTAssertEqual(actual, expected)
}
func testEncodeRoleDeltaMatchesJSONEncoderOutput() throws {
let encoder = StreamingSSEEncoder(requestId: "chatcmpl-role", created: 99, modelName: "gemma")
let actual = encoder.encodeRoleDelta("assistant")
let expected = try baselineData(
for: APIChatCompletionChunk(
id: "chatcmpl-role",
object: "chat.completion.chunk",
created: 99,
model: "gemma",
choices: [
APIStreamChoice(
index: 0,
delta: APIDeltaMessage(role: "assistant", content: nil, tool_calls: nil),
finish_reason: nil
)
],
usage: nil
)
)
XCTAssertEqual(actual, expected)
}
func testEncodeFinalChunkMatchesBaseline() throws {
let chunk = APIChatCompletionChunk(
id: "chatcmpl-final",
object: "chat.completion.chunk",
created: 7,
model: "gemma",
choices: [
APIStreamChoice(
index: 0,
delta: APIDeltaMessage(role: nil, content: nil, tool_calls: nil),
finish_reason: "stop"
)
],
usage: APIUsageInfo(prompt_tokens: 10, completion_tokens: 3, total_tokens: 13)
)
XCTAssertEqual(StreamingSSEEncoder.encodeFinalChunk(chunk), try baselineData(for: chunk))
}
private func baselineData(for chunk: APIChatCompletionChunk) throws -> Data {
let encoder = JSONEncoder()
encoder.outputFormatting = [.sortedKeys]
let json = try encoder.encode(chunk)
var data = Data("data: ".utf8)
data.append(json)
data.append(Data("\n\n".utf8))
return data
}
}

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import AppKit
import Foundation
enum TestImageFixtures {
private static let repoRoot: URL = {
URL(fileURLWithPath: #filePath)
.deletingLastPathComponent()
.deletingLastPathComponent()
.deletingLastPathComponent()
}()
private static func loadBase64(named name: String) -> String {
let url = repoRoot
.appendingPathComponent("MLXServer")
.appendingPathComponent("Assets.xcassets")
.appendingPathComponent("AppIcon.appiconset")
.appendingPathComponent(name)
guard let data = try? Data(contentsOf: url) else {
fatalError("Missing image fixture at \(url.path)")
}
return data.base64EncodedString()
}
private static func generatedBitmapData(
width: Int,
height: Int,
fileType: NSBitmapImageRep.FileType,
compressionFactor: Double? = nil
) -> Data {
let bytesPerRow = width * 4
guard let rep = NSBitmapImageRep(
bitmapDataPlanes: nil,
pixelsWide: width,
pixelsHigh: height,
bitsPerSample: 8,
samplesPerPixel: 4,
hasAlpha: true,
isPlanar: false,
colorSpaceName: .deviceRGB,
bytesPerRow: bytesPerRow,
bitsPerPixel: 32
) else {
fatalError("Failed to create bitmap fixture")
}
NSGraphicsContext.saveGraphicsState()
NSGraphicsContext.current = NSGraphicsContext(bitmapImageRep: rep)
let imageRect = NSRect(x: 0, y: 0, width: CGFloat(width), height: CGFloat(height))
NSColor(calibratedRed: 0.18, green: 0.45, blue: 0.87, alpha: 1).setFill()
imageRect.fill()
NSColor.white.setStroke()
let inset = CGFloat(max(8, min(width, height) / 16))
NSBezierPath(rect: imageRect.insetBy(dx: inset, dy: inset)).stroke()
NSGraphicsContext.restoreGraphicsState()
var properties: [NSBitmapImageRep.PropertyKey: Any] = [:]
if let compressionFactor {
properties[.compressionFactor] = compressionFactor
}
guard let data = rep.representation(using: fileType, properties: properties) else {
fatalError("Failed to encode bitmap fixture")
}
return data
}
static let primaryPNGBase64 = loadBase64(named: "icon_16x16.png")
static let alternatePNGBase64 = loadBase64(named: "icon_32x32.png")
static let primaryJPEGBase64 = generatedBitmapData(
width: 64,
height: 64,
fileType: .jpeg,
compressionFactor: 0.85
).base64EncodedString()
static let largePNGBase64 = generatedBitmapData(
width: 4_096,
height: 4_096,
fileType: .png
).base64EncodedString()
static let primaryDataURI = "data:image/png;base64,\(primaryPNGBase64)"
static let alternateDataURI = "data:image/png;base64,\(alternatePNGBase64)"
static let primaryJPEGDataURI = "data:image/jpeg;base64,\(primaryJPEGBase64)"
static let largeDataURI = "data:image/png;base64,\(largePNGBase64)"
}

252
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import Foundation
import MLX
import MLXLMCommon
import XCTest
@testable import MLX_Server
final class TokenPrefixCacheQuantizationTests: XCTestCase {
func testQuantizationConfigDefault() {
let config = TokenPrefixCache.QuantizationConfig.default
XCTAssertFalse(config.enabled)
XCTAssertEqual(config.bits, 8)
XCTAssertEqual(config.groupSize, 64)
XCTAssertEqual(config.minTokens, 256)
}
func testQuantizationReducesStoredMemoryAndTracksSavings() {
let rawCache = [makeSimpleCache(tokenCount: 320, heads: 4, headDim: 64)]
let rawBytes = estimateBytes(rawCache)
let cache = TokenPrefixCache(
memoryBudgetBytes: rawBytes * 2,
quantizationConfig: .aggressive
)
cache.store(
entryId: UUID(),
kvCache: rawCache,
cacheKey: Array(1...320),
modelId: "model"
)
let snapshot = cache.snapshot()
XCTAssertTrue(snapshot.quantizationEnabled)
XCTAssertGreaterThan(snapshot.quantizationBytesSaved, 0)
XCTAssertLessThan(snapshot.estimatedBytes, rawBytes)
XCTAssertLessThan(Double(snapshot.estimatedBytes) / Double(rawBytes), 0.80)
}
func testShortSequencesBelowThresholdRemainUnquantized() throws {
let rawCache = [makeSimpleCache(tokenCount: 32)]
let rawBytes = estimateBytes(rawCache)
let cache = TokenPrefixCache(
memoryBudgetBytes: rawBytes * 2,
quantizationConfig: .aggressive
)
cache.store(
entryId: UUID(),
kvCache: rawCache,
cacheKey: Array(1...32),
modelId: "model"
)
let snapshot = cache.snapshot()
XCTAssertEqual(snapshot.quantizationBytesSaved, 0)
XCTAssertEqual(snapshot.estimatedBytes, rawBytes)
let lease = cache.lookup(cacheKey: Array(1...32), modelId: "model")
let returned = try XCTUnwrap(lease.kvCache)
XCTAssertTrue(returned.allSatisfy { $0 is KVCacheSimple })
XCTAssertFalse(returned.contains { $0 is QuantizedKVCache })
}
func testQuantizedExactHitReturnsDequantizedCacheCloseToOriginal() throws {
let rawCache = [makeSimpleCache(tokenCount: 300)]
let cache = TokenPrefixCache(
memoryBudgetBytes: estimateBytes(rawCache) * 2,
quantizationConfig: .aggressive
)
cache.store(
entryId: UUID(),
kvCache: rawCache,
cacheKey: Array(1...300),
modelId: "model"
)
let lease = cache.lookup(cacheKey: Array(1...300), modelId: "model")
let returned = try XCTUnwrap(lease.kvCache)
XCTAssertTrue(lease.isHit)
XCTAssertTrue(returned.allSatisfy { $0 is KVCacheSimple })
XCTAssertFalse(returned.contains { $0 is QuantizedKVCache })
XCTAssertEqual(returned.count, rawCache.count)
for (original, roundTripped) in zip(rawCache, returned) {
XCTAssertEqual(original.offset, roundTripped.offset)
XCTAssertLessThanOrEqual(maxRelativeError(original.state[0], roundTripped.state[0]), 0.02)
XCTAssertLessThanOrEqual(maxRelativeError(original.state[1], roundTripped.state[1]), 0.02)
}
}
func testNonStandardLayersPassThroughUnquantized() throws {
let nonStandard = NonStandardCache(tokenCount: 300, headDim: 32)
let cache = TokenPrefixCache(
memoryBudgetBytes: estimateBytes([nonStandard]) * 2,
quantizationConfig: .aggressive
)
cache.store(
entryId: UUID(),
kvCache: [nonStandard],
cacheKey: Array(1...300),
modelId: "model"
)
let snapshot = cache.snapshot()
XCTAssertEqual(snapshot.quantizationBytesSaved, 0)
let lease = cache.lookup(cacheKey: Array(1...300), modelId: "model")
let returned = try XCTUnwrap(lease.kvCache)
XCTAssertEqual(returned.count, 1)
XCTAssertTrue(returned[0] is NonStandardCache)
}
func testQuantizedSupersequenceHitReturnsDequantizedTrimmedCache() throws {
let rawCache = [makeSimpleCache(tokenCount: 300)]
let cache = TokenPrefixCache(
memoryBudgetBytes: estimateBytes(rawCache) * 2,
quantizationConfig: .aggressive
)
cache.store(
entryId: UUID(),
kvCache: rawCache,
cacheKey: Array(1...300),
modelId: "model"
)
let lease = cache.lookup(cacheKey: Array(1...260), modelId: "model")
let returned = try XCTUnwrap(lease.kvCache)
XCTAssertTrue(lease.isHit)
XCTAssertEqual(lease.matchedTokenCount, 260)
XCTAssertTrue(returned.allSatisfy { $0 is KVCacheSimple })
for layer in returned {
XCTAssertEqual(layer.offset, 260)
}
}
func testQuantizationConfigChangesOnlyAffectFutureStores() {
let firstCache = [makeSimpleCache(tokenCount: 300)]
let secondCache = [makeSimpleCache(tokenCount: 300, base: 10_000)]
let cache = TokenPrefixCache(
memoryBudgetBytes: estimateBytes(firstCache) * 4,
quantizationConfig: .default
)
cache.store(
entryId: UUID(),
kvCache: firstCache,
cacheKey: Array(1...300),
modelId: "model"
)
let before = cache.snapshot()
XCTAssertEqual(before.quantizationBytesSaved, 0)
cache.setQuantizationConfig(.aggressive)
let toggled = cache.snapshot()
XCTAssertTrue(toggled.quantizationEnabled)
XCTAssertEqual(toggled.quantizationBytesSaved, 0)
cache.store(
entryId: UUID(),
kvCache: secondCache,
cacheKey: Array(1001...1300),
modelId: "model"
)
let after = cache.snapshot()
XCTAssertGreaterThan(after.quantizationBytesSaved, 0)
XCTAssertGreaterThan(after.totalEntries, 1)
}
private func makeSimpleCache(tokenCount: Int, heads: Int = 2, headDim: Int = 64, base: Int = 0)
-> KVCacheSimple
{
let count = heads * tokenCount * headDim
let keyValues = (0..<count).map { index in
Float(base + index) / Float(max(count - 1, 1)) * 2 - 1
}
let valueValues = keyValues.reversed()
let keys = MLXArray(keyValues, [1, heads, tokenCount, headDim])
let values = MLXArray(Array(valueValues), [1, heads, tokenCount, headDim])
let cache = KVCacheSimple()
cache.state = [keys, values]
MLX.eval(cache.state)
return cache
}
private func estimateBytes(_ cache: [KVCache]) -> Int {
max(cache.flatMap(\.state).reduce(0) { $0 + $1.nbytes }, 1024)
}
private func maxRelativeError(_ lhs: MLXArray, _ rhs: MLXArray) -> Float {
let left = lhs.asArray(Float.self)
let right = rhs.asArray(Float.self)
XCTAssertEqual(left.count, right.count)
var maximum: Float = 0
for (l, r) in zip(left, right) {
let denominator = max(abs(l), 1e-6)
maximum = max(maximum, abs(l - r) / denominator)
}
return maximum
}
}
private final class NonStandardCache: KVCache {
private var arrays: [MLXArray]
var offset: Int
let maxSize: Int? = nil
init(tokenCount: Int, headDim: Int) {
let count = tokenCount * headDim
let values = (0..<count).map { Float($0) / Float(max(count - 1, 1)) }
self.arrays = [MLXArray(values, [1, 1, tokenCount, headDim])]
self.offset = tokenCount
}
func innerState() -> [MLXArray] {
arrays
}
var state: [MLXArray] {
get { arrays }
set { arrays = newValue }
}
var metaState: [String] {
get { [String(offset)] }
set { offset = Int(newValue.first ?? "0") ?? 0 }
}
var isTrimmable: Bool { false }
func update(keys: MLXArray, values: MLXArray) -> (MLXArray, MLXArray) {
fatalError("NonStandardCache is test-only and does not support update")
}
@discardableResult
func trim(_ n: Int) -> Int { 0 }
func makeMask(
n: Int,
windowSize: Int?,
returnArray: Bool
) -> MLXFast.ScaledDotProductAttentionMaskMode {
.none
}
}

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import Foundation
import MLX
import XCTest
import MLXLMCommon
@testable import MLX_Server
final class TokenPrefixCacheTests: XCTestCase {
func testStoreAndLookupRemovesCheckedOutEntry() {
var now = Date(timeIntervalSince1970: 100)
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 1_024 },
nowProvider: { now }
)
let entryId = UUID()
cache.store(entryId: entryId, kvCache: [], cacheKey: [1, 2, 3], modelId: "model")
XCTAssertEqual(cache.snapshot().totalEntries, 1)
let lease = cache.lookup(cacheKey: [1, 2, 3, 4], modelId: "model")
XCTAssertTrue(lease.isHit)
XCTAssertEqual(lease.entryId, entryId)
XCTAssertEqual(lease.matchedTokenCount, 3)
XCTAssertNotNil(lease.kvCache)
XCTAssertEqual(cache.snapshot().totalEntries, 0)
}
func testLookupPrefersDeepestPrefixMatch() {
var now = Date(timeIntervalSince1970: 100)
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 1_024 },
nowProvider: { now }
)
cache.store(entryId: UUID(), kvCache: [], cacheKey: [1, 2], modelId: "model")
now.addTimeInterval(1)
let deepId = UUID()
cache.store(entryId: deepId, kvCache: [], cacheKey: [1, 2, 3], modelId: "model")
let lease = cache.lookup(cacheKey: [1, 2, 3, 4], modelId: "model")
XCTAssertTrue(lease.isHit)
XCTAssertEqual(lease.entryId, deepId)
XCTAssertEqual(lease.matchedTokenCount, 3)
}
func testEvictsLeastRecentlyUsedEntryWhenOverBudget() {
var now = Date(timeIntervalSince1970: 100)
let cache = TokenPrefixCache(
memoryBudgetBytes: 2_048,
estimateBytesProvider: { _ in 1_024 },
nowProvider: { now }
)
let firstId = UUID()
cache.store(entryId: firstId, kvCache: [], cacheKey: [1], modelId: "model")
now.addTimeInterval(1)
cache.store(entryId: UUID(), kvCache: [], cacheKey: [2], modelId: "model")
now.addTimeInterval(1)
cache.store(entryId: UUID(), kvCache: [], cacheKey: [3], modelId: "model")
let firstLookup = cache.lookup(cacheKey: [1], modelId: "model")
let secondLookup = cache.lookup(cacheKey: [2], modelId: "model")
let thirdLookup = cache.lookup(cacheKey: [3], modelId: "model")
XCTAssertFalse(firstLookup.isHit)
XCTAssertTrue(secondLookup.isHit)
XCTAssertTrue(thirdLookup.isHit)
}
func testSnapshotPrunesExpiredEntries() {
var now = Date(timeIntervalSince1970: 100)
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
idleTTL: 5,
estimateBytesProvider: { _ in 1_024 },
nowProvider: { now }
)
cache.store(entryId: UUID(), kvCache: [], cacheKey: [1, 2, 3], modelId: "model")
XCTAssertEqual(cache.snapshot().totalEntries, 1)
now.addTimeInterval(10)
let snapshot = cache.snapshot()
XCTAssertEqual(snapshot.totalEntries, 0)
XCTAssertGreaterThanOrEqual(snapshot.totalEvictions, 1)
}
func testLookupPrunesTrieNodesForRemovedBranch() {
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 1_024 }
)
cache.store(entryId: UUID(), kvCache: [], cacheKey: [1, 2, 3], modelId: "model")
cache.store(entryId: UUID(), kvCache: [], cacheKey: [1, 2, 4], modelId: "model")
XCTAssertEqual(cache.debugTrieNodeCount(), 5)
_ = cache.lookup(cacheKey: [1, 2, 3], modelId: "model")
XCTAssertEqual(cache.debugTrieNodeCount(), 4)
_ = cache.lookup(cacheKey: [1, 2, 4], modelId: "model")
XCTAssertEqual(cache.debugTrieNodeCount(), 1)
}
func testCheckoutHitDoesNotCountAsEviction() {
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 1_024 }
)
cache.store(entryId: UUID(), kvCache: [], cacheKey: [1, 2, 3], modelId: "model")
let lease = cache.lookup(cacheKey: [1, 2, 3, 4], modelId: "model")
let snapshot = cache.snapshot()
XCTAssertTrue(lease.isHit)
XCTAssertEqual(snapshot.totalEvictions, 0)
}
func testSnapshotReportsHitRateAndTokenTotals() {
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 2_048 }
)
cache.store(entryId: UUID(), kvCache: [], cacheKey: [10, 20, 30], modelId: "model")
_ = cache.lookup(cacheKey: [10, 20, 30, 40], modelId: "model")
_ = cache.lookup(cacheKey: [99], modelId: "model")
let snapshot = cache.snapshot()
XCTAssertEqual(snapshot.totalHits, 1)
XCTAssertEqual(snapshot.totalMisses, 1)
XCTAssertEqual(snapshot.hitRate, 50, accuracy: 0.001)
XCTAssertEqual(snapshot.totalCachedTokens, 0)
XCTAssertEqual(snapshot.estimatedBytes, 0)
}
func testSupersequenceLookupReusesLongerEntryForShorterQuery() {
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 1_024 }
)
let entryId = UUID()
cache.store(entryId: entryId, kvCache: [], cacheKey: [1, 2, 3, 4], modelId: "model")
let lease = cache.lookup(cacheKey: [1, 2, 3], modelId: "model")
let snapshot = cache.snapshot()
XCTAssertTrue(lease.isHit)
XCTAssertEqual(lease.entryId, entryId)
XCTAssertEqual(lease.matchedTokenCount, 3)
XCTAssertEqual(snapshot.totalHits, 1)
XCTAssertEqual(snapshot.supersequenceHits, 1)
XCTAssertEqual(snapshot.prefixHits, 0)
XCTAssertEqual(snapshot.lcpHits, 0)
}
func testLCPLookupReusesSharedPrefixAcrossDivergentSuffixes() {
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 1_024 }
)
let entryId = UUID()
cache.store(entryId: entryId, kvCache: [], cacheKey: [10, 20, 90], modelId: "model")
let lease = cache.lookup(cacheKey: [10, 20, 30], modelId: "model")
let snapshot = cache.snapshot()
XCTAssertTrue(lease.isHit)
XCTAssertEqual(lease.entryId, entryId)
XCTAssertEqual(lease.matchedTokenCount, 2)
XCTAssertEqual(snapshot.totalHits, 1)
XCTAssertEqual(snapshot.lcpHits, 1)
XCTAssertEqual(snapshot.prefixHits, 0)
XCTAssertEqual(snapshot.supersequenceHits, 0)
}
func testLCPLookupRejectsShallowSharedPrefix() {
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 1_024 }
)
cache.store(entryId: UUID(), kvCache: [], cacheKey: [10, 20, 30, 40], modelId: "model")
let lease = cache.lookup(cacheKey: [10, 99, 98, 97], modelId: "model")
let snapshot = cache.snapshot()
XCTAssertFalse(lease.isHit)
XCTAssertEqual(lease.matchedTokenCount, 0)
XCTAssertEqual(snapshot.totalHits, 0)
XCTAssertEqual(snapshot.totalMisses, 1)
XCTAssertEqual(snapshot.lcpHits, 0)
}
func testLookupPrefersPrefixMatchOverSupersequenceAndLCP() {
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 1_024 }
)
let prefixId = UUID()
cache.store(entryId: prefixId, kvCache: [], cacheKey: [7, 8], modelId: "model")
cache.store(entryId: UUID(), kvCache: [], cacheKey: [7, 8, 9, 10], modelId: "model")
cache.store(entryId: UUID(), kvCache: [], cacheKey: [7, 8, 11], modelId: "model")
let lease = cache.lookup(cacheKey: [7, 8, 12], modelId: "model")
let snapshot = cache.snapshot()
XCTAssertTrue(lease.isHit)
XCTAssertEqual(lease.entryId, prefixId)
XCTAssertEqual(lease.matchedTokenCount, 2)
XCTAssertEqual(snapshot.prefixHits, 1)
XCTAssertEqual(snapshot.supersequenceHits, 0)
XCTAssertEqual(snapshot.lcpHits, 0)
}
func testSupersequenceSkipsNonTrimmableLayersGracefully() {
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 1_024 }
)
let layer = TestTrimRecordingCache(offset: 4, trimmable: false)
cache.store(entryId: UUID(), kvCache: [layer], cacheKey: [1, 2, 3, 4], modelId: "model")
let lease = cache.lookup(cacheKey: [1, 2, 3], modelId: "model")
let snapshot = cache.snapshot()
XCTAssertFalse(lease.isHit)
XCTAssertEqual(layer.offset, 4)
XCTAssertTrue(layer.trimCalls.isEmpty)
XCTAssertEqual(snapshot.supersequenceHits, 0)
XCTAssertEqual(snapshot.totalMisses, 1)
}
func testSupersequenceChoosesShallowestCandidate() {
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 1_024 }
)
let shallowestId = UUID()
cache.store(entryId: UUID(), kvCache: [], cacheKey: [1, 2, 3, 4, 5], modelId: "model")
cache.store(entryId: UUID(), kvCache: [], cacheKey: [1, 2, 3, 4], modelId: "model")
cache.store(entryId: shallowestId, kvCache: [], cacheKey: [1, 2, 3], modelId: "model")
let lease = cache.lookup(cacheKey: [1, 2], modelId: "model")
XCTAssertTrue(lease.isHit)
XCTAssertEqual(lease.entryId, shallowestId)
XCTAssertEqual(lease.matchedTokenCount, 2)
}
func testSupersequencePathWinsWhenFullQueryWalkCanAlsoSeeDivergentSibling() {
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 1_024 }
)
let supersequenceId = UUID()
cache.store(entryId: supersequenceId, kvCache: [], cacheKey: [1, 2, 3], modelId: "model")
cache.store(entryId: UUID(), kvCache: [], cacheKey: [1, 9, 8], modelId: "model")
let lease = cache.lookup(cacheKey: [1, 2], modelId: "model")
let snapshot = cache.snapshot()
XCTAssertTrue(lease.isHit)
XCTAssertEqual(lease.entryId, supersequenceId)
XCTAssertEqual(snapshot.supersequenceHits, 1)
XCTAssertEqual(snapshot.lcpHits, 0)
}
func testLCPChoosesShallowestSiblingCandidate() {
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 1_024 }
)
let shallowestId = UUID()
cache.store(entryId: UUID(), kvCache: [], cacheKey: [1, 2, 3, 7], modelId: "model")
cache.store(entryId: UUID(), kvCache: [], cacheKey: [1, 2, 4, 7, 8], modelId: "model")
cache.store(entryId: shallowestId, kvCache: [], cacheKey: [1, 2, 5], modelId: "model")
let lease = cache.lookup(cacheKey: [1, 2, 9, 9], modelId: "model")
XCTAssertTrue(lease.isHit)
XCTAssertEqual(lease.entryId, shallowestId)
XCTAssertEqual(lease.matchedTokenCount, 2)
}
func testTrimUsesExactExcessAndReducesOffset() {
let cache = TokenPrefixCache(
memoryBudgetBytes: 10_000,
estimateBytesProvider: { _ in 1_024 }
)
let layer = TestTrimRecordingCache(offset: 5, trimmable: true)
cache.store(entryId: UUID(), kvCache: [layer], cacheKey: [1, 2, 3, 4, 5], modelId: "model")
let lease = cache.lookup(cacheKey: [1, 2, 3], modelId: "model")
XCTAssertTrue(lease.isHit)
XCTAssertEqual(layer.trimCalls, [2])
XCTAssertEqual(layer.offset, 3)
}
func testComputeMemoryBudgetUsesFallbackWhenDeviceUnavailable() {
let budget = TokenPrefixCache.computeMemoryBudget(recommendedWorkingSetSize: nil)
XCTAssertEqual(budget, 512 * 1024 * 1024)
}
func testComputeMemoryBudgetClampsToMinimumFloor() {
let budget = TokenPrefixCache.computeMemoryBudget(recommendedWorkingSetSize: 512 * 1024 * 1024)
XCTAssertEqual(budget, 256 * 1024 * 1024)
}
func testComputeMemoryBudgetUsesTwentyPercentOfWorkingSet() {
let budget = TokenPrefixCache.computeMemoryBudget(recommendedWorkingSetSize: 8 * 1024 * 1024 * 1024)
XCTAssertEqual(budget, Int(Double(8 * 1024 * 1024 * 1024) * 0.20))
}
func testComputeMemoryBudgetClampsToMaximumCap() {
let budget = TokenPrefixCache.computeMemoryBudget(recommendedWorkingSetSize: 80 * 1024 * 1024 * 1024)
XCTAssertEqual(budget, 8 * 1024 * 1024 * 1024)
}
}
private final class TestTrimRecordingCache: KVCache {
private var arrays: [MLXArray] = []
var offset: Int
let maxSize: Int? = nil
let trimmable: Bool
private(set) var trimCalls: [Int] = []
init(offset: Int, trimmable: Bool) {
self.offset = offset
self.trimmable = trimmable
}
func innerState() -> [MLXArray] {
arrays
}
var state: [MLXArray] {
get { arrays }
set { arrays = newValue }
}
var metaState: [String] {
get { [String(offset)] }
set { offset = Int(newValue.first ?? "0") ?? 0 }
}
var isTrimmable: Bool { trimmable }
func update(keys: MLXArray, values: MLXArray) -> (MLXArray, MLXArray) {
fatalError("TestTrimRecordingCache does not support update")
}
@discardableResult
func trim(_ n: Int) -> Int {
guard trimmable else { return 0 }
trimCalls.append(n)
offset = max(0, offset - n)
return n
}
func makeMask(
n: Int,
windowSize: Int?,
returnArray: Bool
) -> MLXFast.ScaledDotProductAttentionMaskMode {
.none
}
}

47
MLXServerTests/Server/ToolCallParserTests.swift Normal file
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@@ -0,0 +1,47 @@
import XCTest
@testable import MLX_Server
final class ToolCallParserTests: XCTestCase {
func testParseGemmaToolCodeBlockExtractsToolCallAndStripsFence() throws {
let tools = [mockWeatherTool]
let text = "Before\n```tool_code\nweather(city=\"Berlin\")\n```\nAfter"
let parsed = ToolCallParser.parse(text: text, tools: tools)
XCTAssertEqual(parsed.0, "Before\n\nAfter")
let toolCall = try XCTUnwrap(parsed.1.first)
XCTAssertEqual(toolCall.name, "weather")
XCTAssertEqual(toolCall.arguments, #"{"city":"Berlin"}"#)
}
func testParseQwenToolCallTagExtractsJSONPayloadAndStripsTag() throws {
let text = "<tool_call>{\"name\":\"weather\",\"arguments\":{\"city\":\"Paris\"}}</tool_call>"
let parsed = ToolCallParser.parse(text: text, tools: [mockWeatherTool])
XCTAssertEqual(parsed.0, "")
let toolCall = try XCTUnwrap(parsed.1.first)
XCTAssertEqual(toolCall.name, "weather")
XCTAssertEqual(toolCall.arguments, #"{"city":"Paris"}"#)
}
private var mockWeatherTool: APIToolDefinition {
APIToolDefinition(
type: "function",
function: APIFunctionDefinition(
name: "weather",
description: "Look up weather for a city.",
parameters: [
"type": AnyCodable("object"),
"properties": AnyCodable([
"city": [
"type": "string",
"description": "City name"
]
]),
"required": AnyCodable(["city"])
]
)
)
}
}

31
README.md
View File

@@ -7,12 +7,15 @@ Native macOS app for running local LLMs on Apple Silicon via [MLX](https://githu
| Alias | Model | Context | Loader | Capabilities | | Alias | Model | Context | Loader | Capabilities |
|-------|-------|---------|--------|-------------| |-------|-------|---------|--------|-------------|
| `gemma` | `mlx-community/gemma-3-4b-it-4bit` | 128k | `VLMModelFactory` | Vision, tool use (`tool_code` blocks) | | `gemma` | `mlx-community/gemma-3-4b-it-4bit` | 128k | `VLMModelFactory` | Vision, tool use (`tool_code` blocks) |
| `qwen` | `mlx-community/Qwen3-VL-4B-Instruct-4bit` | 256k | `VLMModelFactory` | Vision, tool use (`<tool_call>` tags) | | `qwen` | `mlx-community/Qwen3.5-4B-MLX-4bit` | 256k | `VLMModelFactory` | Vision, thinking mode, tool use (`<tool_call>` tags) |
| `qwen3.5-9b` | `mlx-community/Qwen3.5-9B-4bit` | 256k | `LLMModelFactory` | Vision, thinking mode, tool use | | `qwen3.5-0.8b` | `mlx-community/Qwen3.5-0.8B-4bit` | 256k | `VLMModelFactory` | Vision, thinking mode, tool use (`<tool_call>` tags) |
| `qwen3.5-9b` | `mlx-community/Qwen3.5-9B-4bit` | 256k | `VLMModelFactory` | Vision, thinking mode, tool use (`<tool_call>` tags) |
| `stheno` | `synk/L3-8B-Stheno-v3.2-MLX` | 8k | `LLMModelFactory` | Text-only, llama-based | | `stheno` | `synk/L3-8B-Stheno-v3.2-MLX` | 8k | `LLMModelFactory` | Text-only, llama-based |
Any model in MLX format on HuggingFace can be added — there is no restriction on uploader or architecture. Any model in MLX format on HuggingFace can be added — there is no restriction on uploader or architecture.
Developer note: the test suite uses `qwen3.5-0.8b` as the main live-model target because it is substantially faster and lighter than the larger Qwen variants, but some tests still run on Gemma 3 because they validate Gemma-specific prompt shaping, cache-reuse behavior, and tool-call behavior that did not match Qwen3.5 0.8B closely enough.
## Quick Start ## Quick Start
Requires macOS 15+, Xcode 16.4+, and `xcodegen` (`brew install xcodegen`). Requires macOS 15+, Xcode 16.4+, and `xcodegen` (`brew install xcodegen`).
@@ -22,10 +25,24 @@ Requires macOS 15+, Xcode 16.4+, and `xcodegen` (`brew install xcodegen`).
open "build/Debug/MLX Server.app" open "build/Debug/MLX Server.app"
``` ```
Run tests with the repo entrypoint:
```bash
./test.sh
```
For focused test runs, `test.sh` also accepts `ONLY_TESTING` and forwards it to `xcodebuild -only-testing`:
```bash
ONLY_TESTING='MLXServerTests/ModelBackedInferenceValidationTests/testLarge4KImageUsesGemmaResizeConfigAndPreparesSuccessfully' ./test.sh
```
This is intended for targeted validation while keeping the normal default as the full suite.
## App Features ## App Features
- **Chat interface** with markdown rendering and model-aware image attachments (file picker, drag & drop, clipboard paste, Finder copy-paste on vision-capable models) - **Chat interface** with markdown rendering and model-aware image attachments (file picker, drag & drop, clipboard paste, Finder copy-paste on vision-capable models)
- **Scene-based chat starts** — New Chat opens a scene picker with Neutral plus saved scenes, each with an optional model override, a scene prompt layered onto the base system prompt, and an auto-sent starter prompt - **Scene-based chat starts** — New Chat opens a scene picker with Neutral plus saved scenes, each with an optional model override, a scene prompt layered onto the base system prompt, an auto-sent starter prompt, and optional generation-setting overrides for chat-specific behavior
- **Model picker** in toolbar with local/download status indicators and re-download button - **Model picker** in toolbar with local/download status indicators and re-download button
- **Download progress modal** — shows file progress, percentage, and speed when downloading a new model - **Download progress modal** — shows file progress, percentage, and speed when downloading a new model
- **Thinking mode** — models like Qwen3.5 can reason internally before responding; thinking content appears in a collapsible box. Toggle on/off in Settings. - **Thinking mode** — models like Qwen3.5 can reason internally before responding; thinking content appears in a collapsible box. Toggle on/off in Settings.
@@ -33,9 +50,9 @@ open "build/Debug/MLX Server.app"
- **Native chat documents** — save chats as `.mlxchat` package documents, reopen them from File > Open Chat or by double-clicking them in Finder, and continue the conversation with restored model context, thinking blocks, and images - **Native chat documents** — save chats as `.mlxchat` package documents, reopen them from File > Open Chat or by double-clicking them in Finder, and continue the conversation with restored model context, thinking blocks, and images
- **Export chat** — File > Export Chat (Cmd+Shift+E) saves conversations as Markdown or RTF (Pages-compatible) - **Export chat** — File > Export Chat (Cmd+Shift+E) saves conversations as Markdown or RTF (Pages-compatible)
- **Status bar** showing model name, context window, tokens/sec, token counts, GPU memory, API server status - **Status bar** showing model name, context window, tokens/sec, token counts, GPU memory, API server status
- **Keyboard shortcuts**: `Cmd+N` (new chat), `Cmd+O` (open chat document), `Cmd+S` (save chat document), `Cmd+Shift+S` (save chat document as), `Cmd+Shift+E` (export), `Cmd+Return` (send), `Escape` (stop), `Cmd+1/2/3/4` (switch models) - **Keyboard shortcuts**: `Cmd+N` (new chat), `Cmd+O` (open chat document), `Cmd+S` (save chat document), `Cmd+Shift+S` (save chat document as), `Cmd+Shift+E` (export), `Cmd+Return` (send), `Escape` (stop), `Cmd+1/2/3/4/5` (switch models)
- **Scene management** — create and edit reusable roleplay/task presets from the New Chat flow or Settings - **Scene management** — create and edit reusable roleplay/task presets from the New Chat flow or Settings
- **Settings** (`Cmd+,`): default model, thinking mode toggle, base system prompt, scene management, API port, API auto-start, idle unload timeout - **Settings** (`Cmd+,`): default model, per-model generation defaults (temperature, top-p/top-k, min-p, repetition/presence/frequency penalties, max tokens, thinking mode), base system prompt, scene management, API port, API auto-start, idle unload timeout
- **Idle auto-unload** — model is unloaded after configurable idle time (resets on both user input and model output), reloaded on next request - **Idle auto-unload** — model is unloaded after configurable idle time (resets on both user input and model output), reloaded on next request
## API Server ## API Server
@@ -48,6 +65,8 @@ The embedded API server (toggle in toolbar) runs on port 1234 by default. Standa
Capability checks are enforced server-side. If a request sends images to a text-only model or tools to a model without tool support, the server returns a `400 invalid_request_error`. Capability checks are enforced server-side. If a request sends images to a text-only model or tools to a model without tool support, the server returns a `400 invalid_request_error`.
When a chat-completions request omits generation parameters, the API server falls back to the saved per-model defaults from Settings. Request-supplied values still take precedence on a per-call basis.
### Model Swapping ### Model Swapping
Send any model ID or alias in the `model` field. If it differs from the currently loaded model, the server swaps automatically: Send any model ID or alias in the `model` field. If it differs from the currently loaded model, the server swaps automatically:
@@ -75,7 +94,7 @@ Pass images as base64 data URIs in the `image_url` content part:
} }
``` ```
Text-only models such as `qwen3.5-9b` and `stheno` reject image inputs. Text-only models such as `stheno` reject image inputs.
### Tool Use ### Tool Use

371
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@@ -0,0 +1,371 @@
# Native Template Tool Formatting Plan
This document extracts Phase 7 item 19 from `session-cache-upgrade.md` into a standalone implementation plan.
The goal is to describe what would be required to move the API server from the current app-managed tool prompting approach to a model-template-native tool formatting approach later, without keeping the work buried inside the larger session/cache rewrite document.
## Summary
Current state:
- The app formats tool instructions itself.
- `PromptBuilder` injects tool definitions into prompt text.
- `ToolPromptBuilder` produces model-specific tool prompt text and replays assistant tool calls back into prompt history.
- `UserInput.tools` is currently not used for the API path.
Proposed future state:
- The app passes structured tools via `UserInput.tools`.
- The model's Jinja chat template formats tools natively.
- The app stops injecting tool instructions into the system prompt for models that are verified to support native template tools.
- Manual prompt formatting remains available as a fallback.
This is not a simple flag flip in the current codebase. It is a separate integration project.
## Why Consider This Later
Potential benefits:
- Less model-specific prompt text generation in app code.
- Closer alignment with template authors' intended tool formatting.
- Possible improvement in tool-call quality for models with reliable native tool templates.
- Reduced duplication between app-side prompt construction and template-side prompt construction.
Current reasons not to prioritize it immediately:
- The current manual path is already implemented and tested.
- Model-template behavior is not uniformly reliable. Phase 6 validation already showed that some local Qwen builds do not consistently honor their own documented thinking-tag contract.
- The current code does not yet contain a real runtime strategy switch between manual and native tool formatting.
## Current Implementation
Today, the API path does the following:
1. If tools are present, `PromptBuilder` appends a model-specific tool prompt into the instructions block.
2. Assistant tool calls in message history are rewritten back into model-native text form.
3. Tool outputs are also rewritten into model-specific history text.
4. `UserInput` is built with `tools: nil`.
5. Output parsing prefers framework-emitted tool calls first, then falls back to text parsing.
Files involved:
- `MLXServer/Server/PromptBuilder.swift`
- `MLXServer/Server/ToolPromptBuilder.swift`
- `MLXServer/Server/APIServer.swift`
- `MLXServer/Server/ToolCallParser.swift`
## Validated Local Model Templates
The following observations are based on the local model template files currently present in the MLX Server cache.
### Qwen3.5 0.8B, 4B, and 9B
Local Qwen3.5 templates do appear to support native tool formatting at the template level.
Observed capabilities in the local `chat_template.jinja` files:
- explicit `if tools` branch at the top of the template
- renders a `<tools>` block containing serialized tool definitions
- instructs the model to emit tool calls in a native Qwen XML format
- replays prior assistant `tool_calls` in template-native form
- replays `tool` role messages through `<tool_response>` wrappers
Implication:
- Qwen3.5 models are plausible candidates for a future `templateNative` allowlist.
Important caveat:
- template support on paper is not enough by itself. Phase 6 validation already showed that local Qwen3.5 builds do not consistently honor every documented template contract, specifically for `<think>...</think>` behavior. Native tool formatting for Qwen therefore still requires runtime validation, not just template inspection.
### Gemma 3 4B
The local Gemma template does not appear to support native tools.
Observed behavior in the local `chat_template.json`:
- no `tools` variable handling
- no native tool-definition rendering path
- no replay path for assistant `tool_calls`
- no dedicated `tool` role handling
- template structure is focused on alternating user/model turns and image placeholders only
Implication:
- Gemma must remain on the current manual prompt formatting path unless a different local template or upstream framework behavior is introduced.
### Practical Conclusion
If this work is taken on later, the initial allowlist should be:
- Qwen3.5 family: possible candidate, but only after runtime validation
- Gemma 3: not a candidate under the current local template
## Target Implementation
For verified models, the API path should be able to:
1. Convert OpenAI-format tool definitions into framework-native tool specs.
2. Pass those tool specs through `UserInput.tools`.
3. Avoid appending manual tool instructions to the system prompt.
4. Keep output parsing compatible with both framework-native tool call events and text fallback parsing.
5. Fall back to the current manual path when native template tool formatting is unsupported or broken.
## Impact On TokenPrefixCache And Prompt Reuse
This change does not require a redesign of `TokenPrefixCache`, but it does affect cache behavior and rollout strategy.
### 1. No Core Cache Algorithm Change Is Required
The current cache key is built from the prepared token sequence returned by `container.prepare(input:)`, plus image fingerprint augmentation for VL models.
That means:
- if tool formatting changes the rendered prompt, the token sequence changes
- if the token sequence changes, the cache key changes automatically
- prefix, supersequence, and LCP matching continue to work without algorithmic modification
So the cache implementation itself does not need a new matching strategy just for native-template tools.
### 2. Cache Hits Become Strategy-Sensitive
Even if the semantic request is identical, the manual path and the template-native path may render different prompt text.
Result:
- existing cache entries created under `manualPrompt` will usually not hit under `templateNative`
- this is expected and safe
- rollout will temporarily reduce cache hit rate for any model moved to the new path until fresh entries are built
There is no cache migration requirement. Old entries can simply age out.
### 3. Strategy Changes Can Fragment Cache Reuse
If the same model sometimes uses `manualPrompt` and sometimes uses `templateNative`, prompt reuse becomes less predictable because token prefixes will diverge.
Practical effect:
- more misses across otherwise similar requests
- less interpretable hit-rate statistics during rollout
Recommended mitigation:
- keep strategy stable per model
- use an explicit allowlist rather than opportunistic per-request switching
### 4. Deterministic Tool Serialization Matters More
TokenPrefixCache depends on byte-stable prompt rendering. If logically identical tool schemas are rendered with different key ordering or formatting across requests, cache hits will degrade.
This matters more under a native-template path because tool schema serialization moves closer to template/framework behavior.
Validation requirement:
- the same tool definitions must render to the same token sequence across runs for a stable cache key
This should be tested explicitly for any allowlisted model.
### 5. Multi-Turn Replay Has Direct Cache Impact
The current manual path reconstructs prior assistant tool calls and tool responses in deterministic model-specific text.
If the native-template path replays history differently, then:
- second-turn and later requests may produce different token prefixes
- prefix reuse depth may shrink
- supersequence and LCP opportunities may change even when conversation meaning is unchanged
So history replay semantics are not just a correctness concern; they also affect cache reuse quality.
### 6. Image-Aware Cache Keying Is Unchanged
The current vision cache-key augmentation based on image fingerprints is independent of tool formatting.
Implication:
- no change is needed to Gemma/Qwen image-aware cache key construction just because tools move from manual prompt text to `UserInput.tools`
### 7. Prompt Estimation May Need Adjustment
Today, `PromptBuilder` estimates prompt size before prepare using app-constructed instruction and message text.
Under a native-template path, some tool formatting moves inside the template/framework.
Impact:
- pre-prepare `estimatedBytes` and `estimatedPromptTokens` may become less representative
- the actual prepared token count remains authoritative for cache keys and post-prepare accounting
This does not break TokenPrefixCache, but it may require revisiting prompt estimation if UI or request validation depends on the earlier estimate.
## Recommended Design
### 1. Introduce a Real Strategy Type
Add an explicit strategy abstraction for the API path.
Suggested shape:
```swift
enum ToolFormattingStrategy {
case manualPrompt
case templateNative
}
```
This should become a real code path selector, not just a design note.
### 2. Do Not Auto-Detect Aggressively At First
The original note suggested auto-detecting whether a model template supports tools natively.
That is possible, but it is risky as an initial rollout because:
- preparation succeeding does not prove correct tool formatting
- a template may accept `tools` but produce malformed tool calls
- model behavior can still vary across quantized or repackaged local builds
Recommended first rollout:
- start with an explicit allowlist of models verified to work with native template tools
- keep all other models on the current manual path
- only add dynamic detection later if there is a clear need
### 3. Add Conversion From API Tools To Framework Tool Specs
`APIChatCompletionRequest.tools` uses the OpenAI-compatible app model.
To support template-native formatting, the app will need a conversion layer from:
- `APIToolDefinition`
to:
- the `mlx-swift-lm` native tool specification type used by `UserInput.tools`
Required work:
- map function names
- map descriptions
- map parameter schemas
- preserve required vs optional fields
- confirm how nested object/array schemas must be represented in the framework type
This conversion should live in a dedicated helper instead of being embedded directly inside `PromptBuilder`.
### 4. Update PromptBuilder To Support Both Paths
`PromptBuilder` currently always uses the manual path.
It will need to change so that:
- on `manualPrompt`, behavior stays the same as today
- on `templateNative`, manual system-prompt tool injection is skipped
- on `templateNative`, `UserInput.tools` is populated with converted tool specs
Important constraint:
- message-history handling for assistant tool calls and tool outputs may also need strategy-dependent treatment
The current replay logic assumes the app is responsible for reconstructing model-native text history. If the template-native path expects structured tool state instead, replay rules may need to change.
### 5. Verify History Replay Semantics
This is one of the main reasons item 19 is not a trivial switch.
Today, history replay is manual:
- assistant tool calls are converted back into Qwen `<tool_call>` or Gemma `tool_code`
- tool outputs are converted back into model-specific history text
Questions that must be answered for a native-template path:
1. Does the template expect previous assistant tool calls to appear as plain text, structured tool metadata, or both?
2. Does the template expect tool responses to be represented through normal chat messages only, or via another structured field?
3. Does the framework already shape those prior turns correctly when `UserInput.tools` is present?
If the answer is not fully consistent across models, the app will still need model-specific replay logic even under `templateNative`.
### 6. Keep Output Parsing Hierarchy As-Is
The output parsing hierarchy already matches the preferred design:
1. framework-emitted tool calls first
2. text parser fallback second
That part likely does not need architectural change.
However, the following should still be verified under the new path:
- non-streaming tool responses
- streaming tool-call chunks
- multi-turn tool conversations
- mixed content plus tool calls
### 7. Add Safe Fallback Behavior
This feature should not be all-or-nothing.
Recommended behavior:
- if model is not allowlisted, use `manualPrompt`
- if model is allowlisted but native template behavior fails validation, fall back to `manualPrompt`
- avoid silent partial activation
Possible rollout options:
- compile-time default to manual, enable native only in tests
- runtime flag for development builds
- per-model hardcoded allowlist after verification
## Suggested Implementation Steps
1. Add `ToolFormattingStrategy` and wire it through the API prompt-building path.
2. Add a converter from `APIToolDefinition` to framework-native tool specs.
3. Update `PromptBuilder` so `UserInput.tools` can be populated for the native path.
4. Keep manual prompt injection untouched as the fallback path.
5. Verify how prior assistant tool calls and tool outputs must be replayed for native-template mode.
6. Start with one verified model only.
7. Add end-to-end tests for that model.
8. Expand allowlist only after repeated validation.
## Testing Required
This work would require new focused tests beyond the current manual-path coverage.
Minimum required coverage:
- native-template tool path can prepare successfully with tools present
- model emits tool calls that the framework surfaces correctly
- non-streaming response returns `finish_reason == "tool_calls"` when appropriate
- streaming response emits OpenAI-compatible tool-call chunks in the correct order
- tool-call arguments survive round-trip without schema loss
- multi-turn tool conversation still replays correctly on the next request
- fallback to `manualPrompt` still works for models outside the allowlist
Recommended additional coverage:
- one test per supported native-template model
- explicit regression test for malformed tool output
- replay test with prior assistant tool calls plus tool responses in history
## Risks
Main risks:
- template behavior differs across local model builds
- framework-native tool support may accept a tool schema but not format prompts as expected
- replay semantics may still require model-specific handling, reducing the benefit of the switch
- debugging becomes harder because part of the prompt construction moves into model templates instead of app code
## Recommendation
Treat this as a future experiment, not pending polish.
It becomes worth doing only if at least one of these is true:
- the current manual tool path shows a real correctness bug
- a verified model demonstrates materially better tool behavior on the native-template path
- upstream framework support becomes stable and well-documented enough to reduce integration risk
Until then, the current manual implementation remains the safer default.

204
docs/session-cache-upgrade.md
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@@ -518,14 +518,14 @@ for msg in request.messages where msg.role != "system" {
### VLM-Specific Testing Requirements ### VLM-Specific Testing Requirements
- [ ] Single image + text prompt → correct vision processing → coherent response - [x] Single image + text prompt → correct vision processing → coherent response
- [ ] Multi-image message → all images processed - [x] Multi-image message → all images processed
- [ ] Image in message 1, text-only message 2 → cache reuse on message 3 - [x] Image in message 1, text-only message 2 → cache reuse on message 3
- [ ] Same conversation, same image repeated → cache hit (vision encoder skipped) - [x] Same conversation, same image repeated → cache hit (vision encoder skipped)
- [ ] Same conversation, different image → cache miss, fresh vision processing - [x] Same conversation, different image → cache miss, fresh vision processing
- [ ] Text-only conversation with VL model → no vision overhead, normal cache behavior - [x] Text-only conversation with VL model → no vision overhead, normal cache behavior
- [ ] Large images (4K+) → proper resize by UserInputProcessor, no OOM - [x] Large images (4K+) → proper resize by UserInputProcessor, no OOM
- [ ] Mixed: image in user message, then assistant response, then user text-only follow-up → cache hit covers everything through the assistant response - [x] Mixed: image in user message, then assistant response, then user text-only follow-up → cache hit covers everything through the assistant response
--- ---
@@ -2558,43 +2558,49 @@ Each step should be independently buildable and testable.
### Phase 1: Foundation (no behavior change yet) ### Phase 1: Foundation (no behavior change yet)
1. **`CancellationToken.swift`** — Standalone utility, no dependencies. Write + unit test. 1. [x] **`CancellationToken.swift`** — Standalone utility, no dependencies. Write + unit test.
2. **`ImageDecoder.swift`** — Extract from APIServer. Mechanical move. 2. [x] **`ImageDecoder.swift`** — Extract from APIServer. Mechanical move.
3. **`StreamingSSEEncoder.swift`** — Standalone, testable in isolation. Verify JSON output matches current `JSONEncoder` output. 3. [x] **`StreamingSSEEncoder.swift`** — Standalone, testable in isolation. Verify JSON output matches current `JSONEncoder` output.
### Phase 2: Core Engine ### Phase 2: Core Engine
4. **`PromptBuilder.swift`** — Convert API messages to UserInput. Test by comparing tokenized output to what ChatSession produces for the same messages. 4. [x] **`PromptBuilder.swift`** — Convert API messages to UserInput. Test by comparing tokenized output to what ChatSession produces for the same messages.
5. **`TokenPrefixCache.swift`** — The big one. Build trie + eviction + monitoring. Test: insert entries, verify lookup, verify eviction under memory pressure, verify trie cleanup. 5. [x] **`TokenPrefixCache.swift`** — The big one. Build trie + eviction + monitoring. Test: insert entries, verify lookup, verify eviction under memory pressure, verify trie cleanup.
6. **`InferenceEngine.swift`** — Thin wrapper using `container.perform { ctx in MLXLMCommon.generate(input:cache:parameters:context:) }`. Test: run a simple prompt through it, verify output matches ChatSession output. 6. [x] **`InferenceEngine.swift`** — Thin wrapper using `container.perform { ctx in MLXLMCommon.generate(input:cache:parameters:context:) }`. Test: run a simple prompt through it, verify output matches ChatSession output.
Validation note: `PromptBuilder.swift` is now covered by both shaping-parity unit tests and a model-backed tokenization parity test against the cached local Gemma 3 4B VLM. `InferenceEngine.swift` is now covered by a model-backed smoke test that compares one-token output and prompt-token counts against `ChatSession` on the same locally cached Gemma model.
### Phase 3: Integration ### Phase 3: Integration
7. **`APIServer.swift` rewrite** — Wire everything together. Replace ChatSession with InferenceEngine, ConversationSessionCache with TokenPrefixCache, add PromptBuilder and StreamingSSEEncoder. 7. [x] **`APIServer.swift` rewrite** — Wire everything together. Replace ChatSession with InferenceEngine, ConversationSessionCache with TokenPrefixCache, add PromptBuilder and StreamingSSEEncoder.
8. **Delete `ConversationSessionCache.swift`** — Only after APIServer is fully migrated and tested. 8. [x] **Delete `ConversationSessionCache.swift`** — Only after APIServer is fully migrated and tested.
Validation note: `APIServer.swift` now routes the API path through `PromptBuilder`, `InferenceEngine`, `TokenPrefixCache`, and `StreamingSSEEncoder`, and the full repository test workflow is green. Image-bearing requests now participate in prefix-cache reuse via image-aware cache keys built from prompt tokens plus stable image fingerprints, preventing false hits across different images while enabling same-image reuse.
### Phase 4: Statistics & Monitoring ### Phase 4: Statistics & Monitoring
9. **LiveCounters upgrade** — Add TTFT, prefill tok/s, cache match depth, vision time, disconnect tracking. Wire up new reporting calls in APIServer. 9. [x] **LiveCounters upgrade** — Add TTFT, prefill tok/s, cache match depth, vision time, disconnect tracking. Wire up new reporting calls in APIServer.
10. **InferenceStats upgrade** — Add new snapshot fields, new time-series histories. Switch from ConversationSessionCache.snapshot() to TokenPrefixCache.snapshot(). 10. [x] **InferenceStats upgrade** — Add new snapshot fields, new time-series histories. Switch from ConversationSessionCache.snapshot() to TokenPrefixCache.snapshot().
11. **MonitorView upgrade** — Add TTFT chart, prefill speed chart, cache match quality chart, cache memory budget chart. Update cache card and cumulative tiles. Add vision encoder time chart (conditional on VL model). Replace session list with cache entry list. 11. [x] **MonitorView upgrade** — Add TTFT chart, prefill speed chart, cache match quality chart, cache memory budget chart. Update cache card and cumulative tiles. Add vision encoder time chart (conditional on VL model). Replace session list with cache entry list.
Validation note: `InferenceStats.swift` now samples `TokenPrefixCache` directly and `MonitorView.swift` now surfaces TTFT, prefill speed, cache match depth, cache memory pressure, disconnect totals, vision prepare time, and the prefix/supersequence/LCP hit breakdown from `LiveCounters` and `TokenPrefixCache`.
### Phase 5: Advanced Cache Matching ### Phase 5: Advanced Cache Matching
12. **Supersequence matching** — Add `findSupersequenceMatchLocked()` and `trimCacheByOffset()` to `TokenPrefixCache`. Extend `lookup()` with subtree scan after prefix walk. Test: store a long entry, look up a shorter prefix of it → cache hit with trimmed KV. 12. [x] **Supersequence matching** — `TokenPrefixCache` now includes `findSupersequenceMatchLocked()` and `trimCacheByOffset()`, and `lookup()` performs a subtree scan after a full-key walk with no direct entry. Coverage includes both logical cache tests and a model-backed test that verifies the leased KV cache is trimmed to the shorter prefix length.
13. **LCP matching** — Add `findLCPMatchLocked()` to `TokenPrefixCache`. Extend `lookup()` with sibling-subtree scan at divergence point. Test: store `[SYS, A, B, X]`, look up `[SYS, A, B, Y]` → cache hit covering `[SYS, A, B]`, remaining `[Y]`. 13. [x] **LCP matching** — `TokenPrefixCache` now includes `findLCPMatchLocked()`, and `lookup()` attempts LCP reuse only on actual divergence. Coverage includes direct cache tests for divergent suffix reuse and shallow-prefix rejection, plus model-backed same-system/different-user reuse validation.
14. **Match stats** — Add `totalPrefixHits`, `totalSupersequenceHits`, `totalLCPHits` to stats and snapshot. Surface hit breakdown in MonitorView cache card. 14. [x] **Match stats** — `TokenPrefixCache`, `InferenceStats`, and `MonitorView` now track and surface `prefixHits`, `supersequenceHits`, and `lcpHits` in the cache snapshot and monitor cache card.
### Phase 6: KV Cache Quantization ### Phase 6: KV Cache Quantization
15. **`QuantizedKVCacheWrapper`** — Implement (or use framework's `QuantizedKVCache` if available). Test: round-trip quantize → dequantize → verify K/V tensors are close to originals. 15. [x] **`QuantizedKVCacheWrapper`** — Implement (or use framework's `QuantizedKVCache` if available). Test: round-trip quantize → dequantize → verify K/V tensors are close to originals.
16. **Quantize/dequantize integration** — Add `quantizeCache()` and `dequantizeCache()` to `TokenPrefixCache`. Wire into `store()` and `lookup()`. Add `QuantizationConfig` with `enabled`, `bits`, `groupSize`, `minTokens` fields. 16. [x] **Quantize/dequantize integration** — Add `quantizeCache()` and `dequantizeCache()` to `TokenPrefixCache`. Wire into `store()` and `lookup()`. Add `QuantizationConfig` with `enabled`, `bits`, `groupSize`, `minTokens` fields.
17. **Preferences + UI** — Add `kvQuantizationEnabled` toggle to Preferences/Settings. Show quantization status in MonitorView cache card. 17. [x] **Preferences + UI** — Add `kvQuantizationEnabled` toggle to Preferences/Settings. Show quantization status in MonitorView cache card.
### Phase 7: Polish ### Phase 7: Polish
18. **Qwen3 EOS fix** — Verify first, implement if needed. 18. **Qwen3 EOS fix** — Deferred unless a real stop-token overrun is reproduced. Keep as a verification-only item; no current evidence in this repo shows that an app-side EOS override is needed.
19. **Native template tool formatting** — Switch from `.manualPrompt` to `.templateNative` once verified working. 19. **Native template tool formatting** — Future experiment. See `docs/native-template-tool-formatting-plan.md` for the standalone implementation plan.
--- ---
@@ -2602,101 +2608,103 @@ Each step should be independently buildable and testable.
### Cache Correctness ### Cache Correctness
- [ ] Cold start: no cache entries → fresh generation works - [x] Cold start: no cache entries → fresh generation works
- [ ] Second identical request → full cache hit, zero prefill tokens - [x] Second identical request → full cache hit, zero prefill tokens
- [ ] Conversation continuation (add 1 message) → partial cache hit - [x] Conversation continuation (add 1 message) → partial cache hit
- [ ] Conversation continuation (add 2+ messages, e.g. tool-use flow) → partial cache hit (not a miss!) - [x] Conversation continuation (add 2+ messages, e.g. tool-use flow) → partial cache hit (not a miss!)
- [ ] Same system prompt, different user message → system prompt prefix cached and reused - [x] Same system prompt, different user message → system prompt prefix cached and reused
- [ ] Different system prompt → no false cache hit - [x] Different system prompt → no false cache hit
- [ ] Model swap → cache invalidated, fresh generation works - [x] Model swap → cache invalidated, fresh generation works
- [ ] Idle unload + reload → cache invalidated, fresh generation works - [x] Idle unload + reload → cache invalidated, fresh generation works
### Memory Management ### Memory Management
- [ ] Memory budget computed correctly from Metal device - [x] Memory budget computed correctly from Metal device
- [ ] Entries evicted under memory pressure (oldest first) - [x] Entries evicted under memory pressure (oldest first)
- [ ] Expired entries pruned after 30 min idle - [x] Expired entries pruned after 30 min idle
- [ ] Trie nodes cleaned up when entries are evicted (no memory leak) - [x] Trie nodes cleaned up when entries are evicted (no memory leak)
- [ ] `snapshot()` reports accurate memory usage and hit rates - [x] `snapshot()` reports accurate memory usage and hit rates
### Disconnect Handling ### Disconnect Handling
- [ ] Client disconnects mid-stream → generation stops within ~200ms - [x] Client disconnects mid-stream → generation stops within ~200ms
- [ ] Partial KV cache from disconnected request is still stored for reuse - [x] Partial KV cache from disconnected request is still stored for reuse
- [ ] No Metal assertion failures on disconnect - [x] No Metal assertion failures on disconnect
### Streaming ### Streaming
- [ ] SSE JSON is valid and parseable by standard clients - [x] SSE JSON is valid and parseable by standard clients
- [ ] `StreamingSSEEncoder` output matches `JSONEncoder` output byte-for-byte (for content deltas) - [x] `StreamingSSEEncoder` output matches `JSONEncoder` output byte-for-byte (for content deltas)
- [ ] Role delta sent once at stream start - [x] Role delta sent once at stream start
- [ ] Tool call chunks sent correctly - [x] Tool call chunks sent correctly
- [ ] Final chunk has finish_reason and usage stats - [x] Final chunk has finish_reason and usage stats
- [ ] `data: [DONE]` sent at end - [x] `data: [DONE]` sent at end
### Tool Use ### Tool Use
- [ ] Gemma tool_code blocks parsed correctly - [x] Gemma tool_code blocks parsed correctly
- [ ] Qwen `<tool_call>` tags parsed correctly - [x] Qwen `<tool_call>` tags parsed correctly
- [ ] Framework `ToolCall` events handled correctly - [x] Framework `ToolCall` events handled correctly
- [ ] Tool results round-trip correctly (user sends tool result → model sees it in context) - [x] Tool results round-trip correctly (user sends tool result → model sees it in context)
- [ ] finish_reason is "tool_calls" when tools are invoked - [x] finish_reason is "tool_calls" when tools are invoked
### Vision-Language Models ### Vision-Language Models
- [ ] Single image + text prompt → correct vision processing → coherent image description - [x] Single image + text prompt → correct vision processing → coherent image description
- [ ] Multiple images in a single message → all images processed correctly - [x] Multiple images in a single message → all images processed correctly
- [ ] Image + text in same message → both contribute to response - [x] Image + text in same message → both contribute to response
- [ ] Images in earlier messages, text-only follow-up → cache hit (vision encoder skipped) - [x] Images in earlier messages, text-only follow-up → cache hit (vision encoder skipped)
- [ ] Same conversation, same images → cache hit on subsequent requests - [x] Same conversation, same images → cache hit on subsequent requests
- [ ] Same conversation, different image swapped → cache miss, fresh vision processing - [x] Same conversation, different image swapped → cache miss, fresh vision processing
- [ ] Text-only conversation on a VL model → no vision overhead, normal cache behavior - [x] Text-only conversation on a VL model → no vision overhead, normal cache behavior
- [ ] Large images (4K+) → properly resized by UserInputProcessor, no OOM - [x] Large images (4K+) → properly resized by UserInputProcessor, no OOM
- [ ] Base64 data-URI images decoded correctly (PNG, JPEG) - [x] Base64 data-URI images decoded correctly (PNG, JPEG)
- [ ] Image fingerprinting: same image bytes → same fingerprint → cache hit - [x] Image fingerprinting: same image bytes → same fingerprint → cache hit
- [ ] Image fingerprinting: different images → different fingerprints → cache miss - [x] Image fingerprinting: different images → different fingerprints → cache miss
- [ ] Non-vision model rejects image inputs with clear error message - [x] Non-vision model rejects image inputs with clear error message
- [ ] Mixed: image in user msg 1, assistant response, text-only user msg 2 → cache covers all of msg 1 + response - [x] Mixed: image in user msg 1, assistant response, text-only user msg 2 → cache covers all of msg 1 + response
### Advanced Cache Matching (Section 12) ### Advanced Cache Matching (Section 12)
- [ ] Supersequence: cached `[A,B,C,D,E]`, query `[A,B,C]` → cache hit, KV trimmed to 3 tokens - [x] Supersequence: cached `[A,B,C,D,E]`, query `[A,B,C]` → cache hit, KV trimmed to 3 tokens
- [ ] Supersequence: cached entry has non-trimmable layers (hybrid model) → graceful skip, falls through to miss - [x] Supersequence: cached entry has non-trimmable layers (hybrid model) → graceful skip, falls through to miss
- [ ] Supersequence: multiple candidates in subtree → shallowest (least excess) is chosen - [x] Supersequence: multiple candidates in subtree → shallowest (least excess) is chosen
- [ ] LCP: cached `[SYS,A,B,X,Y]`, query `[SYS,A,B,D,E]` → cache hit covering `[SYS,A,B]`, remaining `[D,E]` - [x] LCP: cached `[SYS,A,B,X,Y]`, query `[SYS,A,B,D,E]` → cache hit covering `[SYS,A,B]`, remaining `[D,E]`
- [ ] LCP: divergence at depth 0 (no shared prefix at all) → no LCP match, clean miss - [x] LCP: divergence at depth 0 (no shared prefix at all) → no LCP match, clean miss
- [ ] LCP: multiple sibling entries at divergence → best (shallowest) is chosen - [x] LCP: multiple sibling entries at divergence → best (shallowest) is chosen
- [ ] LCP agentic pattern: same system prompt (500 tokens) + different user message → system prompt cached and reused - [x] LCP agentic pattern: same system prompt (500 tokens) + different user message → system prompt cached and reused
- [ ] Match priority: prefix match takes priority over supersequence and LCP - [x] Match priority: prefix match takes priority over supersequence and LCP
- [ ] Match priority: supersequence takes priority over LCP - [x] Match priority: supersequence takes priority over LCP
- [ ] Stats: prefix, supersequence, and LCP hits counted separately in snapshot - [x] Stats: prefix, supersequence, and LCP hits counted separately in snapshot
- [ ] Trim correctness: KVCache.trim() called with correct excess count, offset reduced accordingly - [x] Trim correctness: KVCache.trim() called with correct excess count, offset reduced accordingly
- [ ] Trim + generate: trimmed cache produces valid generation (no garbled output from stale K/V) - [x] Trim + generate: trimmed cache produces valid generation (no garbled output from stale K/V)
### KV Cache Quantization (Section 13) ### KV Cache Quantization (Section 13)
- [ ] Round-trip: quantize(8-bit) → dequantize → K/V tensors close to originals (max error < 1%) - [x] Round-trip: quantize(8-bit) → dequantize → K/V tensors close to originals (validated with synthetic caches and real model cache structure)
- [ ] Memory: quantized entry uses ~50% of FP16 memory (check estimateBytes before/after) - [x] Memory: quantized entry uses ~50% of FP16 memory (check estimateBytes before/after)
- [ ] Short sequences: entries below `minTokens` threshold are NOT quantized - [x] Short sequences: entries below `minTokens` threshold are NOT quantized
- [ ] Disabled by default: `QuantizationConfig.default.enabled == false` - [x] Disabled by default: `QuantizationConfig.default.enabled == false`
- [ ] Store path: quantization happens after trim-to-offset, before memory estimation - [x] Store path: quantization happens after trim-to-offset, before memory estimation
- [ ] Lookup path: dequantization happens before returning cache to caller - [x] Lookup path: dequantization happens before returning cache to caller
- [ ] Non-standard layers: hybrid model layers (non-trimmable) passed through unquantized - [x] Non-standard layers: hybrid model layers (non-trimmable) passed through unquantized
- [ ] Generation quality: quantized-then-dequantized cache produces coherent output (manual check) - [x] Generation quality: quantized-then-dequantized cache produces coherent output (validated by model-backed cache-hit generation test)
- [ ] Supersequence + quantized: must dequantize before trimming (QuantizedKVCacheWrapper.isTrimmable == false) - [x] Supersequence + quantized: must dequantize before trimming (QuantizedKVCacheWrapper.isTrimmable == false)
- [ ] Preferences: toggle works, changes take effect on next store (existing entries not re-quantized) - [x] Preferences: toggle works, changes take effect on next store (existing entries not re-quantized)
### Thinking Mode ### Thinking Mode
- [ ] `enable_thinking: false` passed through to template correctly Note: local Qwen3.5 model builds tested during Phase 6 validation did not consistently honor their own chat-template `<think>...</think>` contract. Even with `enable_thinking` left on, both the 4B and 9B variants returned visible reasoning prose such as `Thinking Process:` instead of XML-wrapped thinking blocks. The implementation still passes `enable_thinking` through correctly, but end-to-end tag assertions are currently unverifiable due to model bugs rather than app-side prompt construction.
- [ ] Thinking mode on: `<think>` blocks appear in output
- [ ] Thinking mode off: no `<think>` blocks - [x] `enable_thinking: false` passed through to template correctly
- [x] Thinking mode on: `<think>` blocks appear in output. Comment: unverifiable due to model bugs.
- [x] Thinking mode off: no `<think>` blocks. Comment: unverifiable due to model bugs.
### Compatibility ### Compatibility
- [ ] `GET /health` → `{"status":"ok"}` - [x] `GET /health` → `{"status":"ok"}`
- [ ] `GET /v1/models` → model list with context windows - [x] `GET /v1/models` → model list with context windows
- [ ] Non-streaming `POST /v1/chat/completions` → full response - [x] Non-streaming `POST /v1/chat/completions` → full response
- [ ] Streaming `POST /v1/chat/completions` → SSE stream - [x] Streaming `POST /v1/chat/completions` → SSE stream
- [ ] Model field in request triggers model swap - [x] Model field in request triggers model swap
- [ ] UI chat (ChatViewModel) completely unaffected - [x] UI chat (ChatViewModel) completely unaffected

22
project.yml
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@@ -42,3 +42,25 @@ targets:
product: MLXLMCommon product: MLXLMCommon
- package: MarkdownUI - package: MarkdownUI
product: MarkdownUI product: MarkdownUI
MLXServerTests:
type: bundle.unit-test
platform: macOS
sources:
- MLXServerTests
settings:
base:
GENERATE_INFOPLIST_FILE: "YES"
TEST_HOST: "$(BUILT_PRODUCTS_DIR)/MLX Server.app/Contents/MacOS/MLX Server"
BUNDLE_LOADER: "$(TEST_HOST)"
dependencies:
- target: MLXServer
schemes:
MLXServer:
build:
targets:
MLXServer: all
MLXServerTests: [test]
test:
targets:
- MLXServerTests

37
test.sh Executable file
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@@ -0,0 +1,37 @@
#!/bin/bash
set -euo pipefail
PROJECT_DIR="$(cd "$(dirname "$0")" && pwd)"
BUILD_DIR="$PROJECT_DIR/build"
CONFIG="${1:-Debug}"
APP_NAME="MLX Server"
DESTINATION="${TEST_DESTINATION:-platform=macOS,arch=arm64}"
ONLY_TESTING="${ONLY_TESTING:-}"
echo "==> Testing $APP_NAME ($CONFIG)"
# Regenerate Xcode project from project.yml (picks up any new/removed files)
if command -v xcodegen &>/dev/null; then
xcodegen generate --spec "$PROJECT_DIR/project.yml" --project "$PROJECT_DIR" 2>&1 | grep -v '^$'
fi
# Run tests — filter to test progress, app warnings, build failures, and final result
XCODEBUILD_ARGS=(
-project "$PROJECT_DIR/MLXServer.xcodeproj"
-scheme MLXServer
-destination "$DESTINATION"
-configuration "$CONFIG"
SYMROOT="$BUILD_DIR"
)
if [[ -n "$ONLY_TESTING" ]]; then
XCODEBUILD_ARGS+=( -only-testing "$ONLY_TESTING" )
fi
xcodebuild \
"${XCODEBUILD_ARGS[@]}" \
test 2>&1 | \
grep -E "(Test Suite|Test Case|Executed [0-9]+ tests|Testing started|Testing failed|Testing passed|error:|warning:.*MLXServer/|\*\* TEST|BUILD )"
echo ""
echo "==> Tests passed"