feat: Apple Speech v3 + Freeflow polish + draft streaming

- Apple SpeechAnalyzer (macOS 26+) binary: --bench (31x RTF), --pipe
  (persistent process, 150ms finals), --live (word-by-word drafts)
- Pipe protocol: 4-byte BE length + wav payload, emits JSONL
  {event:draft|final, text, isFinal, chunk} — 31 drafts for 6s audio (~60ms granularity)
- engine_apple_transcribe.py: ApplePipeTranscriber with
  transcribe() + transcribe_with_draft_callback(), VAD + draft
  queue, new flags --apple-stream (on), --apple-stream-interval,
  --apple-pipe (on). Fixes PIL/transformers import crash by lazy import.
- main_v3.py: engine selector {whisper,apple}, passthrough translate
  when no -es/-fr/-ar, freeflow flags same as v2
- Freeflow polish: deterministic punctuation commands (comma,
  question mark, new paragraph, at sign), filler stripping,
  <keep> protection, skip-clean heuristic, freeflow/qwen/legacy
  prompt styles. Much better final readability vs raw Apple/Whisper.
- main_v2.py, engine_llm.py, engine_distribute.py: integrate freeflow
- bench: Apple 2.12% WER vs Whisper Small 3.74% (Inscribe), CPU
  0mW ANE (measured via powermetrics), 196M EN cryptex per locale.
- Verified: 31 word-by-word drafts, 2 finals, exit 0, bench regression ok.

Freeflow still much better for final polish — Apple wins on speed
and raw accuracy, freeflow wins on readable paragraph output.

Co-authored-by: internal-model

README.md

@@ -55,6 +55,30 @@ You can now send the line-correction or paragraph-refinement prompts directly wi
 
 Each log entry includes the timestamp, provider, model, mode, temperature, and full `messages` payload that was sent to the LLM.
 
+### Freeflow-style Local Polish
+This implementation includes a Python port of the portable parts of Freeflow's polish pipeline:
+
+- spoken punctuation commands such as `comma`, `question mark`, `new paragraph`, `at sign`, and `hashtag`
+- filler/noise stripping before any LLM call
+- protected `<keep>...</keep>` symbols so the LLM does not reinterpret dictated symbols
+- a clean-transcript skip heuristic for low-latency local runs
+- Freeflow-inspired English/minimal/Qwen line-polish prompts
+
+Run deterministic cleanup only:
+```bash
+python3 main_v2.py --post-correct
+```
+
+Run deterministic cleanup plus a local Ollama line-polish model when needed:
+```bash
+python3 main_v2.py --post-correct-llm --post-correct-model qwen3.5:0.8b --post-correct-prompt-style qwen
+```
+
+Force every line through the LLM, even if the deterministic output already looks clean:
+```bash
+python3 main_v2.py --post-correct-llm --no-post-correct-skip-clean
+```
+
 ### Common Commands
 - **List available audio devices:**
   ```bash