initial commit

backend_cli.py

@@ -0,0 +1,93 @@
+#!/usr/bin/env python3
+"""
+Single CLI entrypoint for the bundled summarizer backend.
+
+This wrapper lets the Tauri app launch one helper executable in production
+while still supporting direct Python execution during development.
+"""
+
+import argparse
+import json
+import sys
+from pathlib import Path
+
+from translate_summary import translate_summary_text
+from youtube_summarizer import process_video
+
+
+DEFAULT_MODEL = "mistral:latest"
+
+
+def configure_stdio() -> None:
+    """Keep progress output line-buffered for the desktop app."""
+    if hasattr(sys.stdout, "reconfigure"):
+        sys.stdout.reconfigure(line_buffering=True)
+    if hasattr(sys.stderr, "reconfigure"):
+        sys.stderr.reconfigure(line_buffering=True)
+
+
+def summarize(args: argparse.Namespace) -> int:
+    meta = process_video(
+        args.url,
+        use_whisper=args.use_whisper,
+        model=args.model,
+        output_json=args.output_json,
+    )
+    if not args.output_json:
+        print(json.dumps(meta, ensure_ascii=False), flush=True)
+    return 0
+
+
+def translate(args: argparse.Namespace) -> int:
+    summary_path = Path(args.summary_file)
+    summary_text = summary_path.read_text(encoding="utf-8").strip()
+    if not summary_text:
+        raise SystemExit("Empty summary text!")
+
+    translation = translate_summary_text(summary_text, args.lang, args.model)
+
+    if args.output_file:
+        Path(args.output_file).write_text(translation, encoding="utf-8")
+    else:
+        print(translation, flush=True)
+    return 0
+
+
+def build_parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(description="Bundled backend for YouTube Summarizer")
+    subparsers = parser.add_subparsers(dest="command", required=True)
+
+    summarize_parser = subparsers.add_parser("summarize", help="Summarize a YouTube video")
+    summarize_parser.add_argument("--url", required=True, help="YouTube video URL")
+    summarize_parser.add_argument("--model", default=DEFAULT_MODEL, help="Ollama model to use")
+    summarize_parser.add_argument(
+        "--no-whisper",
+        dest="use_whisper",
+        action="store_false",
+        help="Use transcript/subtitle workflows instead of Whisper",
+    )
+    summarize_parser.add_argument(
+        "--output-json",
+        help="Write the result metadata to a JSON file instead of stdout",
+    )
+    summarize_parser.set_defaults(use_whisper=True, handler=summarize)
+
+    translate_parser = subparsers.add_parser("translate", help="Translate an English summary")
+    translate_parser.add_argument("--summary-file", required=True, help="Path to the English summary text")
+    translate_parser.add_argument("--lang", required=True, choices=["de", "jp"], help="Target language")
+    translate_parser.add_argument("--model", default=DEFAULT_MODEL, help="Ollama model to use")
+    translate_parser.add_argument("--output-file", help="Optional path to write the translated text")
+    translate_parser.set_defaults(handler=translate)
+
+    return parser
+
+
+def main() -> int:
+    configure_stdio()
+    parser = build_parser()
+    args = parser.parse_args()
+    return args.handler(args)
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())