perf(asr): speed up local Flow dictation and land CLM/keyboard refactor

Reduce perceived latency from key release to final text:
- Adaptive chunking: 2.5s first chunk + 5s follow-ups so short
  utterances start on-device recognition while still recording.
- Session-level ASR warmup and audio-format cache reuse to remove
  per-utterance cold-start of SpeechAnalyzer.
- Mirror live pipelined partials to the keyboard transcript line via
  a new flow.transcriptionPartial App Group key + Darwin ping.

Also commits the accumulated custom language model, Flow session,
keyboard extension restructure, and Xiaomi MiMo provider work in
progress on this branch.

OSGKeyboardShared/Services/FlowSessionDarwin.swift

@@ -8,6 +8,8 @@ import Foundation
 
 public enum FlowSessionDarwin {
     public static let notificationName = "com.osgkeyboard.flow.session.changed"
+    /// Posted when the host app writes a transcription result or error.
+    public static let transcriptionNotificationName = "com.osgkeyboard.flow.transcription.changed"
 
     public static func postSessionChanged() {
         CFNotificationCenterPostNotification(
@@ -18,6 +20,16 @@ public enum FlowSessionDarwin {
             true
         )
     }
+
+    public static func postTranscriptionChanged() {
+        CFNotificationCenterPostNotification(
+            CFNotificationCenterGetDarwinNotifyCenter(),
+            CFNotificationName(transcriptionNotificationName as CFString),
+            nil,
+            nil,
+            true
+        )
+    }
 }
 
 /// Observes Darwin notifications on a background thread; invokes