Initial CutScript release - Open-source AI-powered text-based video editor

CutScript is a local-first, Descript-like video editor where you edit video by editing text.
Delete a word from the transcript and it's cut from the video.

Features:
- Word-level transcription with WhisperX
- Text-based video editing with undo/redo
- AI filler word removal (Ollama/OpenAI/Claude)
- AI clip creation for shorts
- Waveform timeline with virtualized transcript
- FFmpeg stream-copy (fast) and re-encode (4K) export
- Caption burn-in and sidecar SRT generation
- Studio Sound audio enhancement (DeepFilterNet)
- Keyboard shortcuts (J/K/L, Space, Delete, Ctrl+Z/S/E)
- Encrypted API key storage
- Project save/load (.aive files)

Architecture:
- Electron + React + Tailwind (frontend)
- FastAPI + Python (backend)
- WhisperX for transcription
- FFmpeg for video processing
- Multi-provider AI support

Performance optimizations:
- RAF-throttled time updates
- Zustand selectors for granular subscriptions
- Dual-canvas waveform rendering
- Virtualized transcript with react-virtuoso

Built on top of DataAnts-AI/VideoTranscriber, completely rewritten as a desktop application.

License: MIT

backend/routers/transcribe.py

@@ -0,0 +1,53 @@
+"""Transcription endpoint using WhisperX."""
+
+import logging
+from typing import Optional
+
+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel
+
+from services.transcription import transcribe_audio
+from services.diarization import diarize_and_label
+
+logger = logging.getLogger(__name__)
+router = APIRouter()
+
+
+class TranscribeRequest(BaseModel):
+    file_path: str
+    model: str = "base"
+    language: Optional[str] = None
+    use_gpu: bool = True
+    use_cache: bool = True
+    diarize: bool = False
+    hf_token: Optional[str] = None
+    num_speakers: Optional[int] = None
+
+
+@router.post("/transcribe")
+async def transcribe(req: TranscribeRequest):
+    try:
+        result = transcribe_audio(
+            file_path=req.file_path,
+            model_name=req.model,
+            use_gpu=req.use_gpu,
+            use_cache=req.use_cache,
+            language=req.language,
+        )
+
+        if req.diarize and req.hf_token:
+            result = diarize_and_label(
+                transcription_result=result,
+                audio_path=req.file_path,
+                hf_token=req.hf_token,
+                num_speakers=req.num_speakers,
+                use_gpu=req.use_gpu,
+            )
+
+        return result
+
+    except FileNotFoundError:
+        raise HTTPException(status_code=404, detail=f"File not found: {req.file_path}")
+    except Exception as e:
+        logger.error(f"Transcription failed: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))