383e85c05e
Move model and pipeline components into dedicated modules Extract utilities from CLI into shared helpers Update imports throughout codebase Refactor project structure for modularity Move model configuration and hardware selection into `models/` package Extract pipeline steps into `pipeline/` package Add utility helpers in `utils/` package Update CLI imports and references
88 lines
2.5 KiB
Python
88 lines
2.5 KiB
Python
"""Command-line entrypoint.
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Download (optional), transcribe, and summarize audio/video files fully on
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Apple Silicon via MLX. Models are selected automatically from the detected
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unified memory (see ``models.config`` and ``models.device``).
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"""
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import argparse
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from pathlib import Path
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from .models import select_models
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from .pipeline import download_from_youtube, summarize_text, transcribe_file
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from .utils import (
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ensure_directory,
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print_model_banner,
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resolve_language,
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write_summary,
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)
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def _parse_args() -> argparse.Namespace:
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parser = argparse.ArgumentParser(
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description="Download, transcribe, and summarize audio or video files "
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"on Apple Silicon (MLX)."
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)
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group = parser.add_mutually_exclusive_group(required=True)
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group.add_argument("--from-youtube", type=str, help="YouTube URL to download.")
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group.add_argument("--from-local", type=str, help="Path to the local audio file.")
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parser.add_argument(
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"--output",
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type=str,
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default="./summary.md",
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help="Output markdown file path.",
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)
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parser.add_argument(
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"--transcript-only",
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action="store_true",
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help="Only transcribe the file, do not summarize.",
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)
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parser.add_argument(
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"--language",
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type=str,
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help="Language code for transcription (e.g. 'en', 'fr', 'es', "
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"or 'auto' for detection).",
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)
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return parser.parse_args()
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def main() -> None:
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args = _parse_args()
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language = resolve_language(args.language)
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# --- Automatic model selection based on detected unified memory ---
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ram_gb, tier = select_models()
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print_model_banner(ram_gb, tier)
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# --- Working directory for intermediate files ---
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data_directory = ensure_directory("tmp")
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# --- Resolve input file ---
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if args.from_youtube:
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print(f"Downloading YouTube video from {args.from_youtube}")
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file_path = download_from_youtube(args.from_youtube, str(data_directory))
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else:
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file_path = Path(args.from_local)
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# --- Transcription ---
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print(f"Transcribing file: {file_path}")
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transcript = transcribe_file(
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str(file_path),
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str(data_directory / "transcript.txt"),
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tier.stt,
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language,
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)
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if args.transcript_only:
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print("Transcription complete. Skipping summary generation.")
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return
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# --- Summarization ---
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print("Generating summary...")
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summary = summarize_text(transcript, tier.summarization_repo)
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write_summary(args.output, summary)
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if __name__ == "__main__":
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main()
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