Swift 6 Complete Concurrency Checking

Package.swift

@@ -10,6 +10,12 @@
 
 import PackageDescription
 
+#if swift(<6)
+let swiftConcurrency: SwiftSetting = .enableExperimentalFeature("StrictConcurrency")
+#else
+let swiftConcurrency: SwiftSetting = .enableUpcomingFeature("StrictConcurrency")
+#endif
+
 
 let package = Package(
     name: "SpeziLLM",
@@ -45,6 +51,9 @@ let package = Package(
                 .product(name: "Spezi", package: "Spezi"),
                 .product(name: "SpeziChat", package: "SpeziChat"),
                 .product(name: "SpeziViews", package: "SpeziViews")
+            ],
+            swiftSettings: [
+                swiftConcurrency
             ]
         ),
         .target(
@@ -60,6 +69,9 @@ let package = Package(
                 .product(name: "MLXRandom", package: "mlx-swift"),
                 .product(name: "Transformers", package: "swift-transformers"),
                 .product(name: "LLM", package: "mlx-swift-examples")
+            ],
+            swiftSettings: [
+                swiftConcurrency
             ]
         ),
         .target(
@@ -69,6 +81,9 @@ let package = Package(
                 .product(name: "SpeziViews", package: "SpeziViews"),
                 .target(name: "SpeziLLMLocal"),
                 .product(name: "LLM", package: "mlx-swift-examples")
+            ],
+            swiftSettings: [
+                swiftConcurrency
             ]
         ),
         .target(
@@ -81,6 +96,9 @@ let package = Package(
                 .product(name: "SpeziChat", package: "SpeziChat"),
                 .product(name: "SpeziSecureStorage", package: "SpeziStorage"),
                 .product(name: "SpeziOnboarding", package: "SpeziOnboarding")
+            ],
+            swiftSettings: [
+                swiftConcurrency
             ]
         ),
         .target(
@@ -89,12 +107,18 @@ let package = Package(
                 .target(name: "SpeziLLM"),
                 .product(name: "Spezi", package: "Spezi"),
                 .product(name: "OpenAI", package: "OpenAI")
+            ],
+            swiftSettings: [
+                swiftConcurrency
             ]
         ),
         .testTarget(
             name: "SpeziLLMTests",
             dependencies: [
                 .target(name: "SpeziLLMOpenAI")
+            ],
+            swiftSettings: [
+                swiftConcurrency
             ]
         )
     ]

Sources/SpeziLLM/Helpers/LLMContext+Chat.swift

@@ -6,7 +6,7 @@
 // SPDX-License-Identifier: MIT
 //
 
-import SpeziChat
+@preconcurrency import SpeziChat
 
 
 extension LLMContext {

Sources/SpeziLLM/LLMPlatformState.swift

@@ -10,7 +10,7 @@
 /// Describes the current state of the ``LLMPlatform`` which is responsible for sending ``LLMSchema``s to execution via ``LLMSession``s.
 /// 
 /// The ``LLMPlatformState`` is quite minimal with only ``LLMPlatformState/idle`` and ``LLMPlatformState/processing`` states.
-public enum LLMPlatformState {
+public enum LLMPlatformState: Sendable {
     /// Indicates that the ``LLMPlatform`` is currently idle and doesn't execute any ``LLMSession``s.
     case idle
     /// Indicates that the ``LLMPlatform`` is currently processing and executing ``LLMSession``s.

Sources/SpeziLLM/LLMSessionProvider.swift

@@ -45,7 +45,7 @@ public struct _LLMSessionProvider<Schema: LLMSchema>: DynamicProperty {     // s
     }
 
     /// Creates a `Binding` to the ``LLMSession``that one can pass around. Useful for passing the ``LLMSession`` as a `Binding` to the ``LLMChatView``.
-    public var projectedValue: Binding<Schema.Platform.Session> {
+    @MainActor public var projectedValue: Binding<Schema.Platform.Session> {
         Binding {
             wrappedValue
         } set: {

Sources/SpeziLLM/Models/LLMContextEntity.swift

@@ -14,9 +14,9 @@ import Foundation
 /// A ``LLMContextEntity`` can be thought of as a single message entity within a ``LLMContext``
 /// It consists of a ``LLMContextEntity/Role``, a unique identifier, a timestamp in the form of a `Date` as well as an `String`-based ``LLMContextEntity/content`` property which can contain Markdown-formatted text.
 /// Furthermore, the ``LLMContextEntity/complete`` flag indicates if the current state of the ``LLMContextEntity`` is final and the content will not be updated anymore.
-public struct LLMContextEntity: Codable, Equatable, Hashable, Identifiable {
+public struct LLMContextEntity: Codable, Equatable, Hashable, Identifiable, Sendable {
     /// Represents a tool call by the LLM, including its parameters
-    public struct ToolCall: Codable, Equatable, Hashable {
+    public struct ToolCall: Codable, Equatable, Hashable, Sendable {
         /// The ID of the function call, uniquely identifying the specific function call and matching the response to it.
         public let id: String
         /// The name of the function call.
@@ -39,7 +39,7 @@ public struct LLMContextEntity: Codable, Equatable, Hashable, Identifiable {
     }
 
     /// Indicates which ``LLMContextEntity/Role`` is associated with a ``LLMContextEntity``.
-    public enum Role: Codable, Equatable, Hashable {
+    public enum Role: Codable, Equatable, Hashable, Sendable {
         case user
         case assistant(toolCalls: [ToolCall] = [])
         case system

Sources/SpeziLLMFog/LLMFogSession+Generation.swift

@@ -12,14 +12,7 @@ import SpeziChat
 
 
 extension LLMFogSession {
-    private static let modelNotFoundRegex: Regex = {
-        guard let regex = try? Regex("model '([\\w:]+)' not found, try pulling it first") else {
-            preconditionFailure("SpeziLLMFog: Error Regex could not be parsed")
-        }
-
-        return regex
-    }()
-
+    private static let modelNotFoundRegex = "model '([\\w:]+)' not found, try pulling it first"
 
     /// Based on the input prompt, generate the output via some OpenAI API, e.g., Ollama.
     ///
@@ -61,7 +54,7 @@ extension LLMFogSession {
             }
         } catch let error as APIErrorResponse {
             // Sadly, there's no better way to check the error messages as there aren't any Ollama error codes as with the OpenAI API
-            if error.error.message.contains(Self.modelNotFoundRegex) {
+            if error.error.message.range(of: Self.modelNotFoundRegex, options: .regularExpression) != nil {
                 Self.logger.error("SpeziLLMFog: LLM model type could not be accessed on fog node - \(error.error.message)")
                 await finishGenerationWithError(LLMFogError.modelAccessError(error), on: continuation)
             } else if error.error.code == "401" || error.error.code == "403" {