Adolfo Reyna
80f0bf309f
- 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
153 lines
9.1 KiB
Python
153 lines
9.1 KiB
Python
import multiprocessing
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import argparse
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import json
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import os
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import sys
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from dotenv import load_dotenv
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# Load environment variables from .env if present
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load_dotenv()
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# Light imports (heavy ones moved inside run functions)
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from engine_transcribe import run_transcription, list_audio_devices
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from engine_llm import run_llm_processor, run_llm_prompt_test
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from engine_translate import run_translation
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from engine_distribute import run_distribution
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def parse_temperature_fallback(value):
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try:
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return tuple(float(x.strip()) for x in value.split(",") if x.strip())
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except:
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return (0.0, 0.2, 0.4, 0.6, 0.8, 1.0)
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def main():
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config_path = "config.json"
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defaults = {}
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if os.path.exists(config_path):
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with open(config_path, "r") as f:
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defaults = json.load(f)
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parser = argparse.ArgumentParser(description="Multi-process Transcription and Translation.")
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# Transcribe Args
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parser.add_argument("-l", "--list-devices", action="store_true", help="Show available audio devices and exit")
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parser.add_argument("--model", type=str, default=defaults.get("model", "mlx-community/whisper-base-mlx"))
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parser.add_argument("--device", type=int, default=defaults.get("device"))
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parser.add_argument("--lang", type=str, default=defaults.get("lang"))
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parser.add_argument("--silence", type=int, default=defaults.get("silence", 1000))
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parser.add_argument("--max-buffer", type=int, default=defaults.get("max_buffer", 20))
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parser.add_argument("--channels", type=int, default=defaults.get("channels", 1))
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parser.add_argument("--filter-lang", action="store_true", default=defaults.get("filter_lang", False))
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parser.add_argument("-q", "--quantize", action="store_true", default=defaults.get("quantize", False))
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parser.add_argument("-s", "--stream", action="store_true", default=defaults.get("stream", False))
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parser.add_argument("-c", "--context", action="store_true", default=defaults.get("context", False))
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parser.add_argument("--speaker-diarization", action="store_true", default=defaults.get("speaker_diarization", False))
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parser.add_argument("--temperature-fallback", type=parse_temperature_fallback, default=tuple(defaults.get("temperature_fallback", [0.0, 0.2, 0.4, 0.6, 0.8, 1.0])))
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parser.add_argument("--logprob-threshold", type=float, default=defaults.get("logprob_threshold", -0.8))
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parser.add_argument("--compression-threshold", type=float, default=defaults.get("compression_threshold", 2.2))
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# LLM Args
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parser.add_argument("--post-correct", action="store_true", default=defaults.get("post_correct", False))
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parser.add_argument("--post-correct-llm", action="store_true", default=defaults.get("post_correct_llm", False))
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parser.add_argument("--post-correct-model", type=str, default=defaults.get("post_correct_model", "qwen3.5:0.8b"))
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parser.add_argument("--post-correct-ollama-url", type=str, default=defaults.get("post_correct_ollama_url", "http://127.0.0.1:11434/api/generate"))
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parser.add_argument("--post-correct-llm-timeout", type=float, default=defaults.get("post_correct_llm_timeout", 8.0))
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parser.add_argument("--post-correct-keep-alive", type=str, default=defaults.get("post_correct_keep_alive", "30m"))
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parser.add_argument("--post-correct-warmup-timeout", type=float, default=defaults.get("post_correct_warmup_timeout", 20.0))
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parser.add_argument("--post-correct-min-overlap", type=float, default=defaults.get("post_correct_min_overlap", 0.45))
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parser.add_argument("--post-correct-debug", action="store_true", default=defaults.get("post_correct_debug", False))
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parser.add_argument("--freeflow-polish", action="store_true", default=defaults.get("freeflow_polish", True), help="Use Freeflow-style deterministic punctuation/filler polishing before optional LLM cleanup.")
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parser.add_argument("--no-freeflow-polish", action="store_false", dest="freeflow_polish", help="Use the older local regex cleanup instead of Freeflow-style deterministic polishing.")
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parser.add_argument("--post-correct-skip-clean", action="store_true", default=defaults.get("post_correct_skip_clean", True), help="Skip the line LLM when deterministic polish already looks clean.")
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parser.add_argument("--no-post-correct-skip-clean", action="store_false", dest="post_correct_skip_clean", help="Always call the line LLM when --post-correct-llm is enabled.")
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parser.add_argument("--post-correct-prompt-style", choices=["freeflow", "qwen", "legacy"], default=defaults.get("post_correct_prompt_style", "freeflow"), help="Prompt style for line LLM cleanup.")
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parser.add_argument("--llm-paragraph", action="store_true", default=defaults.get("llm_paragraph", False))
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parser.add_argument("--llm-paragraph-temperature", type=float, default=defaults.get("llm_paragraph_temperature", 0.2))
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parser.add_argument("--llm-paragraph-top-p", type=float, default=defaults.get("llm_paragraph_top_p", 0.8))
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parser.add_argument("--llm-paragraph-repeat-penalty", type=float, default=defaults.get("llm_paragraph_repeat_penalty", 1.0))
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parser.add_argument("--llm-request-log-path", type=str, default=defaults.get("llm_request_log_path", "logs/llm_requests.jsonl"))
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parser.add_argument("--llm-test-line", type=str, default=None, help="Send a single line-correction prompt without starting transcription.")
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parser.add_argument("--llm-test-prev1", type=str, default="", help="Optional previous line 1 context for --llm-test-line.")
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parser.add_argument("--llm-test-prev2", type=str, default="", help="Optional previous line 2 context for --llm-test-line.")
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parser.add_argument("--llm-test-segments", type=str, default=None, help="Send a single paragraph-refinement prompt without starting transcription.")
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parser.add_argument("--llm-test-context", type=str, default="", help="Optional existing paragraph context for --llm-test-segments.")
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parser.add_argument("--llm-test-from-log", type=int, default=None, help="Replay a logged LLM request by JSONL entry index. Use -1 for the most recent entry.")
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parser.add_argument("--llm-test-use-logged-model", action="store_true", default=False, help="When replaying from log, use the model stored in the log entry instead of --post-correct-model.")
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# Translate Args
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parser.add_argument("-es", action="store_true", default=defaults.get("es", False))
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parser.add_argument("-fr", action="store_true", default=defaults.get("fr", False))
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parser.add_argument("-ar", action="store_true", default=defaults.get("ar", False))
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parser.add_argument("-en", action="store_true", default=defaults.get("en", False))
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parser.add_argument("--only-translate-llm", action="store_true", default=defaults.get("only_translate_llm", False), help="Only translate when the LLM produces a refined paragraph.")
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parser.add_argument("--mt-max-chars", type=int, default=defaults.get("mt_max_chars", 250))
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parser.add_argument("--mt-max-new-tokens", type=int, default=defaults.get("mt_max_new_tokens", 150))
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parser.add_argument("--mt-num-beams", type=int, default=defaults.get("mt_num_beams", 4))
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# Distribute Args
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parser.add_argument("-i", "--ingest", action="store_true", default=defaults.get("ingest", False))
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args = parser.parse_args()
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# Auto-enable required flags
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if args.post_correct_llm and not args.post_correct:
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args.post_correct = True
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if args.only_translate_llm and not args.llm_paragraph:
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print("[Main] Enabling --llm-paragraph because --only-translate-llm was requested.")
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args.llm_paragraph = True
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if args.llm_test_line or args.llm_test_segments or args.llm_test_from_log is not None:
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run_llm_prompt_test(args)
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return
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# Handle device listing
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if args.list_devices:
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list_audio_devices()
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return
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# Handle interactive device selection
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if args.device is None:
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list_audio_devices()
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try:
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val = input("\nSelect input device index (or press Enter for default): ").strip()
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if val:
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args.device = int(val)
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except EOFError:
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pass # Non-interactive environment
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except ValueError:
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print("[Main] Invalid index, using default.")
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# Queues
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q_trans_to_llm = multiprocessing.Queue()
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q_llm_to_tl = multiprocessing.Queue()
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q_tl_to_dist = multiprocessing.Queue()
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# Processes
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p_transcribe = multiprocessing.Process(target=run_transcription, args=(q_trans_to_llm, args))
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p_llm = multiprocessing.Process(target=run_llm_processor, args=(q_trans_to_llm, q_llm_to_tl, args))
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p_translate = multiprocessing.Process(target=run_translation, args=(q_llm_to_tl, q_tl_to_dist, args))
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p_distribute = multiprocessing.Process(target=run_distribution, args=(q_tl_to_dist, args))
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print("[Main] Starting processes...")
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p_transcribe.start()
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p_llm.start()
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p_translate.start()
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p_distribute.start()
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try:
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p_transcribe.join()
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p_llm.join()
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p_translate.join()
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p_distribute.join()
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except KeyboardInterrupt:
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print("\n[Main] Stopping processes...")
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p_transcribe.terminate()
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p_llm.terminate()
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p_translate.terminate()
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p_distribute.terminate()
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sys.exit(0)
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if __name__ == "__main__":
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multiprocessing.freeze_support()
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main()
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