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.

OSGKeyboardTests/UtteranceStreamChunkerTests.swift

@@ -24,6 +24,30 @@ final class UtteranceStreamChunkerTests: XCTestCase {
         XCTAssertLessThanOrEqual(split, config.maxChunkSamples + config.pauseExtensionSamples)
     }
 
+    func testFirstChunkUsesShorterWindow() async {
+        let config = FlowUtteranceChunkConfig(
+            firstChunkDurationSeconds: 0.5,
+            subsequentChunkDurationSeconds: 1.0,
+            overlapDurationSeconds: 0,
+            pauseExtensionMaxSeconds: 0,
+            pauseRMSThreshold: 0.02,
+            sampleRate: 1_000
+        )
+        let firstChunkSamples = config.maxChunkSamples(forChunkIndex: 0) + 50
+        let samples = [Float](repeating: 0.05, count: firstChunkSamples)
+        let (stream, continuation) = AsyncStream<AudioBufferSnapshot>.makeStream()
+        continuation.yield(AudioBufferSnapshot(samples: samples, sampleRate: Double(config.sampleRate)))
+        continuation.finish()
+
+        var received: [UtteranceAudioChunk] = []
+        for await chunk in UtteranceStreamChunker.chunks(from: stream, config: config) {
+            received.append(chunk)
+        }
+
+        XCTAssertGreaterThanOrEqual(received.count, 2)
+        XCTAssertLessThanOrEqual(received[0].samples.count, config.maxChunkSamples(forChunkIndex: 0) + 50)
+    }
+
     func testChunksEmitMultipleSegmentsForLongStream() async {
         let sampleCount = config.maxChunkSamples * 2 + 100
         let samples = [Float](repeating: 0.05, count: sampleCount)