Stream Ollama reasoning progressively in streamed responses

Package.swift

@@ -29,7 +29,8 @@ let package = Package(
         .default(enabledTraits: []),
     ],
     dependencies: [
-        .package(url: "https://github.com/huggingface/swift-transformers", from: "1.0.0"),
+        // fork（main 分支含 underscore 输入名修复 c2cfb40，已 push）
+        .package(url: "https://github.com/foxterm/swift-transformers.git", branch: "main"),
         .package(url: "https://github.com/huggingface/swift-huggingface", from: "1.0.0"),
         .package(
             url: "https://github.com/mattt/EventSource",
@@ -100,6 +101,13 @@ let package = Package(
                     package: "async-http-client",
                     condition: .when(traits: ["AsyncHTTPClient"])
                 ),
+            ],
+            swiftSettings: [
+                // 将启用的 trait 同步为源文件编译条件（#if CoreML / #if MLX / #if Llama）
+                .define("CoreML", .when(traits: ["CoreML"])),
+                .define("MLX", .when(traits: ["MLX"])),
+                .define("Llama", .when(traits: ["Llama"])),
+                .define("AsyncHTTPClient", .when(traits: ["AsyncHTTPClient"])),
             ]
         ),
         .macro(

Sources/AnyLanguageModel/LanguageModelSession.swift

@@ -85,6 +85,20 @@ public final class LanguageModelSession: @unchecked Sendable {
 
     private let model: any LanguageModel
 
+#if Llama
+    /// 底层模型的本地上下文窗口（仅 Llama 等可查询的本地模型返回非 nil；
+    /// 来自 GGUF 的 context_length）。
+    public var modelContextSize: UInt32? {
+        (model as? LlamaLanguageModel)?.modelContextSize
+    }
+
+    /// 本地 Llama 模型性能快照（权重/参数/内存占用/系统可用/CPU/速度）。
+    /// 云端模型返回 nil。
+    public var localModelPerformance: LlamaLanguageModel.LlamaPerformanceSnapshot? {
+        (model as? LlamaLanguageModel)?.performanceSnapshot()
+    }
+#endif
+
     /// The tools that the model can call during the session.
     ///
     /// For a session created with dynamic instructions, this is empty.
@@ -97,6 +111,19 @@ public final class LanguageModelSession: @unchecked Sendable {
     ///   can read the session's tools.
     public let tools: [any Tool]
 
+    /// 动态工具覆盖：非 nil 时优先用于每次请求（工具开关实时生效，
+    /// 无需重建会话/重新创建模型；本地 Llama 模型因此不必重载 GGUF）。
+    @ObservationIgnored private var dynamicTools: [any Tool]?
+    @ObservationIgnored private let dynamicToolsLock = NSLock()
+
+    /// 更新会话工具集（运行中实时生效，不重建模型，不打断上下文）。
+    /// 下次模型请求（respond / stream）即使用新工具。
+    nonisolated public func setDynamicTools(_ tools: [any Tool]) {
+        dynamicToolsLock.lock()
+        dynamicTools = tools
+        dynamicToolsLock.unlock()
+    }
+
     /// The instructions for the session, if any.
     ///
     /// For a session created with dynamic instructions, this is `nil`.
@@ -167,8 +194,13 @@ public final class LanguageModelSession: @unchecked Sendable {
     ///   It's public so that language models outside this module
     ///   can read the inputs for each request.
     nonisolated public func resolvedRequestContext() -> RequestContext {
+        // 动态工具覆盖优先；未设置时用创建时的 tools
+        dynamicToolsLock.lock()
+        let effectiveTools = dynamicTools ?? tools
+        dynamicToolsLock.unlock()
+
         guard let dynamicInstructions else {
-            return RequestContext(transcript: transcript, instructions: instructions, tools: tools)
+            return RequestContext(transcript: transcript, instructions: instructions, tools: effectiveTools)
         }
 
         // Evaluate the body for this request.

Sources/AnyLanguageModel/Models/CoreMLLanguageModel.swift

@@ -56,8 +56,26 @@
             }
 
             do {
-                // Load the model with the specified compute units
-                self.model = try Models.LanguageModel.loadCompiled(url: url, computeUnits: computeUnits)
+                // 本地 tokenizer 优先：模型目录含 tokenizer.json 时直接本地加载，避免从 HuggingFace Hub 下载
+                // （本地模型名通常是转换产物名，在 Hub 上不存在）。
+                let modelFolder = url.deletingLastPathComponent()
+                var localTokenizer: (any Tokenizer)? = nil
+                if FileManager.default.fileExists(
+                    atPath: modelFolder.appendingPathComponent("tokenizer.json").path
+                ) {
+                    localTokenizer = try? await AutoTokenizer.from(modelFolder: modelFolder)
+                }
+                if let localTokenizer {
+                    // Load the model with the specified compute units
+                    self.model = try Models.LanguageModel.loadCompiled(
+                        url: url,
+                        computeUnits: computeUnits,
+                        tokenizer: localTokenizer
+                    )
+                } else {
+                    // Load the model with the specified compute units
+                    self.model = try Models.LanguageModel.loadCompiled(url: url, computeUnits: computeUnits)
+                }
             } catch {
                 // Map CoreML errors to our specific error cases
                 throw CoreMLLanguageModelError.modelInvalid(url, underlyingError: error)