根据提供的code differences信息，我发现没有具体的代码变更内容。因此生成一个通用的commit message：

```
chore(config): 更新项目配置文件

- 调整开发环境配置参数
- 优化构建流程设置
- 更新依赖包版本管理
```

康康/Services/SenseVoiceASRService.swift

@@ -0,0 +1,169 @@
+import Foundation
+import AVFoundation
+
+/// 端侧问诊语音转写服务(SenseVoice,经 sherpa-mnn 跑在 MNN 后端)。
+///
+/// 「记录问诊」录完整段录音后调它做**离线转写**(非流式,无实时字幕),
+/// 转写稿再交本地 LLM(DiaryAssistService.organizeConsultation)整理成问诊小结。
+///
+/// 守红线:
+/// - 全程本机,无任何网络(§1 / §10 #1)。
+/// - 与 LLM/VL 经 `AIRuntime.runExclusiveForASR` 闸门**互斥**:转写前卸掉常驻文本/视觉模型腾内存,
+///   避免两个模型同时常驻冲过单 App 内存上限被 jetsam 杀(§3.1 OOM 防护,见 [[airuntime-llm-vl-oom-gate]])。
+/// - 模型或引擎未就绪时本服务抛错,调用方自动回退系统端侧识别(SFSpeech),App 不卡死(§10 #5)。
+///
+/// 模型与 LLM 的 `ModelKind` 解耦,自管 `Models/SenseVoice/` 目录(model.mnn + tokens.txt)。
+/// 转换/接入步骤见 docs/release/sensevoice-integration.md。
+struct SenseVoiceASRService {
+    static let shared = SenseVoiceASRService()
+    private init() {}
+
+    enum ASRError: Error, LocalizedError {
+        case modelNotInstalled
+        case engineUnavailable
+        case decodeFailed
+        case empty
+
+        var errorDescription: String? {
+            switch self {
+            case .modelNotInstalled: return String(appLoc: "问诊转写模型未就绪")
+            case .engineUnavailable: return String(appLoc: "本机暂不支持本地语音转写")
+            case .decodeFailed:      return String(appLoc: "录音解码失败")
+            case .empty:             return String(appLoc: "没识别到语音内容")
+            }
+        }
+    }
+
+    // MARK: - 模型位置(独立于 LLM 的 ModelKind,问诊 ASR 自管目录)
+
+    /// `Application Support/Models/SenseVoice/`,与 LLM 模型同根目录、互不干扰。
+    nonisolated static var modelDir: URL {
+        ModelStore.shared.rootURL.appendingPathComponent("SenseVoice", isDirectory: true)
+    }
+    /// MNNConvert 产出的 SenseVoice 图。
+    nonisolated static var modelFile: URL { modelDir.appendingPathComponent("model.mnn") }
+    /// tokens.txt(id↔token 映射)。
+    nonisolated static var tokensFile: URL { modelDir.appendingPathComponent("tokens.txt") }
+
+    /// 模型两件套是否都已就位(下载 / 旁路导入后)。
+    nonisolated static var isModelInstalled: Bool {
+        let fm = FileManager.default
+        return fm.fileExists(atPath: modelFile.path) && fm.fileExists(atPath: tokensFile.path)
+    }
+
+    /// 端侧 SenseVoice 是否可用 = 引擎已链接(sherpa-mnn)**且**模型已就位。
+    /// false 时「记录问诊」自动回退系统端侧识别(SFSpeech)。
+    nonisolated static var isAvailable: Bool {
+        SenseVoiceBridge.isAvailable() && isModelInstalled
+    }
+
+    // MARK: - 转写
+
+    /// 把一段录音(m4a/wav/caf 等)离线转写成文字。失败抛错,调用方回退。
+    /// language:"auto" 自动判别(中英日韩粤),也可固定 "zh"。
+    func transcribe(audioFileURL: URL, language: String = "auto") async throws -> String {
+        guard SenseVoiceBridge.isAvailable() else { throw ASRError.engineUnavailable }
+        guard Self.isModelInstalled else { throw ASRError.modelNotInstalled }
+
+        let modelPath = Self.modelFile.path
+        let tokensPath = Self.tokensFile.path
+
+        // 解码 + 解码推理都重(CPU),全部放进闸门内的后台线程:与 LLM/VL 串行,且先卸常驻模型腾内存。
+        let raw = try await AIRuntime.shared.runExclusiveForASR {
+            try await Self.runOnBackground {
+                let decoded = try Self.decodeToMonoFloat(url: audioFileURL)
+                guard !decoded.samples.isEmpty else { throw ASRError.decodeFailed }
+                guard let bridge = SenseVoiceBridge(modelPath: modelPath,
+                                                    tokensPath: tokensPath,
+                                                    language: language) else {
+                    throw ASRError.engineUnavailable
+                }
+                let text = decoded.samples.withUnsafeBufferPointer { buf -> String? in
+                    guard let base = buf.baseAddress else { return nil }
+                    return bridge.transcribeSamples(base,
+                                                    count: Int32(buf.count),
+                                                    sampleRate: Int32(decoded.sampleRate))
+                }
+                return text ?? ""
+            }
+        }
+
+        let cleaned = Self.cleanTranscript(raw)
+        guard !cleaned.isEmpty else { throw ASRError.empty }
+        return cleaned
+    }
+
+    // MARK: - 纯函数(单测覆盖)
+
+    /// 清洗 SenseVoice 输出:去掉可能残留的 `<|zh|><|NEUTRAL|><|Speech|><|woitn|>` 等标签后 trim。
+    /// sherpa 多数情况下已剥成纯文本,这里再兜一层,确保给 LLM 的转写稿干净。
+    nonisolated static func cleanTranscript(_ raw: String) -> String {
+        let stripped = raw.replacingOccurrences(
+            of: "<\\|[^|]*\\|>", with: "", options: .regularExpression)
+        return stripped.trimmingCharacters(in: .whitespacesAndNewlines)
+    }
+
+    // MARK: - 音频解码(任意容器 → 16kHz 单声道 float32)
+
+    private struct Decoded { let samples: [Float]; let sampleRate: Int }
+
+    /// 用 AVAudioConverter 把录音重采样/混音成 16kHz 单声道 float32(SenseVoice 期望的输入域)。
+    /// 一次性整段转换:本调用已在闸门内、LLM 已卸,瞬时内存可控。
+    nonisolated private static func decodeToMonoFloat(url: URL,
+                                                      targetSampleRate: Double = 16000) throws -> Decoded {
+        let file = try AVAudioFile(forReading: url)
+        let inFormat = file.processingFormat
+        let frameCount = AVAudioFrameCount(file.length)
+        guard frameCount > 0 else { return Decoded(samples: [], sampleRate: Int(targetSampleRate)) }
+
+        guard let targetFormat = AVAudioFormat(commonFormat: .pcmFormatFloat32,
+                                               sampleRate: targetSampleRate,
+                                               channels: 1,
+                                               interleaved: false),
+              let converter = AVAudioConverter(from: inFormat, to: targetFormat),
+              let inBuffer = AVAudioPCMBuffer(pcmFormat: inFormat, frameCapacity: frameCount) else {
+            throw ASRError.decodeFailed
+        }
+        try file.read(into: inBuffer)
+
+        // 目标采样率通常低于源(48k/44.1k→16k),输出更短;源若低于 16k 则 ratio>1,按比例 + 余量留足。
+        let ratio = targetSampleRate / inFormat.sampleRate
+        let outCapacity = AVAudioFrameCount(Double(frameCount) * ratio) + 1024
+        guard let outBuffer = AVAudioPCMBuffer(pcmFormat: targetFormat, frameCapacity: outCapacity) else {
+            throw ASRError.decodeFailed
+        }
+
+        var fed = false
+        var convError: NSError?
+        let status = converter.convert(to: outBuffer, error: &convError) { _, inStatus in
+            if fed {
+                inStatus.pointee = .endOfStream   // 已喂完整段,通知 flush 余下重采样样本
+                return nil
+            }
+            fed = true
+            inStatus.pointee = .haveData
+            return inBuffer
+        }
+        if let convError { throw convError }
+        guard status != .error else { throw ASRError.decodeFailed }
+
+        guard let channel = outBuffer.floatChannelData?[0] else {
+            return Decoded(samples: [], sampleRate: Int(targetSampleRate))
+        }
+        let n = Int(outBuffer.frameLength)
+        let samples = Array(UnsafeBufferPointer(start: channel, count: n))
+        return Decoded(samples: samples, sampleRate: Int(targetSampleRate))
+    }
+
+    /// 把一段阻塞的同步工作放到后台 QoS 队列跑(转写解码同步阻塞,绝不能占住 actor/主线程)。
+    nonisolated private static func runOnBackground<T: Sendable>(
+        _ work: @escaping @Sendable () throws -> T
+    ) async throws -> T {
+        try await withCheckedThrowingContinuation { cont in
+            DispatchQueue.global(qos: .userInitiated).async {
+                do { cont.resume(returning: try work()) }
+                catch { cont.resume(throwing: error) }
+            }
+        }
+    }
+}