feat: implement vertical crop, local LLM deepseek-v4-flash, multi-threading, word-level pink box highlight subtitles, and Nextcloud scan sync

2026-07-02 16:12:23 +02:00
parent 50bdaedebb
commit c7c3c4b74a
154 changed files with 36256 additions and 3 deletions
@@ -0,0 +1,123 @@
+"""End-to-end orchestrator.
+
+Two modes:
+  * mode="api"   (default) — MuAPI does download / transcribe / LLM / autocrop.
+                              Fast, no local deps, pay-per-call.
+  * mode="local"            — yt-dlp + faster-whisper + OpenAI or Gemini + ffmpeg/opencv.
+                              Self-hosted, LLM_PROVIDER selects OpenAI or Gemini.
+"""
+from typing import Dict, List, Optional
+
+from .clipper import crop_highlights
+from .downloader import download_youtube
+from .highlights import call_muapi_llm, get_highlights
+from .transcriber import transcribe
+
+
+def _run_local(
+    youtube_url: str,
+    num_clips: int,
+    aspect_ratio: str,
+    download_format: str,
+    language: Optional[str],
+) -> Dict:
+    from .local.clipper import crop_highlights_local
+    from .local.downloader import download_youtube_local
+    from .local.llm import call_local_llm
+    from .local.transcriber import transcribe_local
+
+    source_path = download_youtube_local(youtube_url, fmt=download_format)
+
+    transcript = transcribe_local(source_path, language=language)
+    if not transcript["segments"]:
+        raise RuntimeError(
+            "Whisper produced no segments. The video may have no detectable speech."
+        )
+
+    highlights_result = get_highlights(transcript, num_clips=num_clips, llm_fn=call_local_llm)
+    all_highlights: List[Dict] = highlights_result.get("highlights", [])
+    if not all_highlights:
+        raise RuntimeError("Highlight generator returned zero clips.")
+
+    top = sorted(all_highlights, key=lambda h: int(h.get("score", 0)), reverse=True)[:num_clips]
+    print(f"[pipeline/local] cropping {len(top)} of {len(all_highlights)} candidates", flush=True)
+
+    shorts = crop_highlights_local(source_path, top, aspect_ratio=aspect_ratio)
+
+    return {
+        "mode": "local",
+        "source_video_url": source_path,
+        "transcript": transcript,
+        "highlights": all_highlights,
+        "shorts": shorts,
+    }
+
+
+def _run_api(
+    youtube_url: str,
+    num_clips: int,
+    aspect_ratio: str,
+    download_format: str,
+    language: Optional[str],
+) -> Dict:
+    source_url = download_youtube(youtube_url, fmt=download_format)
+
+    transcript = transcribe(source_url, language=language)
+    if not transcript["segments"]:
+        raise RuntimeError(
+            "Whisper produced no segments. The video may have no detectable speech."
+        )
+
+    highlights_result = get_highlights(transcript, num_clips=num_clips, llm_fn=call_muapi_llm)
+    all_highlights: List[Dict] = highlights_result.get("highlights", [])
+    if not all_highlights:
+        raise RuntimeError("Highlight generator returned zero clips.")
+
+    top = sorted(all_highlights, key=lambda h: int(h.get("score", 0)), reverse=True)[:num_clips]
+    print(f"[pipeline] cropping {len(top)} of {len(all_highlights)} candidates", flush=True)
+
+    shorts = crop_highlights(source_url, top, aspect_ratio=aspect_ratio)
+
+    return {
+        "mode": "api",
+        "source_video_url": source_url,
+        "transcript": transcript,
+        "highlights": all_highlights,
+        "shorts": shorts,
+    }
+
+
+def generate_shorts(
+    youtube_url: str,
+    num_clips: int = 3,
+    aspect_ratio: str = "9:16",
+    download_format: str = "720",
+    language: Optional[str] = None,
+    mode: str = "api",
+) -> Dict:
+    """Run the full pipeline and return a structured result.
+
+    Args:
+        youtube_url: source URL.
+        num_clips: how many shorts to render.
+        aspect_ratio: e.g. "9:16", "1:1".
+        download_format: source resolution ("360" / "480" / "720" / "1080").
+        language: ISO-639-1 to force Whisper language detection.
+        mode: "api" (default, MuAPI) or "local" (yt-dlp + faster-whisper +
+            OpenAI or Gemini + ffmpeg).
+
+    Returns:
+        {
+          "mode": "api" | "local",
+          "source_video_url": str,   # hosted URL (api) or local path (local)
+          "transcript": {...},
+          "highlights": [...],       # all candidates ranked
+          "shorts": [...],           # top `num_clips` with clip_url / local path
+        }
+    """
+    mode = (mode or "api").lower()
+    if mode == "local":
+        return _run_local(youtube_url, num_clips, aspect_ratio, download_format, language)
+    if mode == "api":
+        return _run_api(youtube_url, num_clips, aspect_ratio, download_format, language)
+    raise ValueError(f"Unknown mode: {mode!r}. Use 'api' or 'local'.")