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/ai.py

@@ -0,0 +1,83 @@
+"""AI feature endpoints: filler word detection, clip creation, Ollama model listing."""
+
+import logging
+from typing import List, Optional
+
+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel
+
+from services.ai_provider import AIProvider, detect_filler_words, create_clip_suggestion
+
+logger = logging.getLogger(__name__)
+router = APIRouter()
+
+
+class WordInfo(BaseModel):
+    index: int
+    word: str
+    start: Optional[float] = None
+    end: Optional[float] = None
+
+
+class FillerRequest(BaseModel):
+    transcript: str
+    words: List[WordInfo]
+    provider: str = "ollama"
+    model: Optional[str] = None
+    api_key: Optional[str] = None
+    base_url: Optional[str] = None
+    custom_filler_words: Optional[str] = None
+
+
+class ClipRequest(BaseModel):
+    transcript: str
+    words: List[WordInfo]
+    provider: str = "ollama"
+    model: Optional[str] = None
+    api_key: Optional[str] = None
+    base_url: Optional[str] = None
+    target_duration: int = 60
+
+
+@router.post("/ai/filler-removal")
+async def filler_removal(req: FillerRequest):
+    try:
+        words_dicts = [w.model_dump() for w in req.words]
+        result = detect_filler_words(
+            transcript=req.transcript,
+            words=words_dicts,
+            provider=req.provider,
+            model=req.model,
+            api_key=req.api_key,
+            base_url=req.base_url,
+            custom_filler_words=req.custom_filler_words,
+        )
+        return result
+    except Exception as e:
+        logger.error(f"Filler detection failed: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.post("/ai/create-clip")
+async def create_clip(req: ClipRequest):
+    try:
+        words_dicts = [w.model_dump() for w in req.words]
+        result = create_clip_suggestion(
+            transcript=req.transcript,
+            words=words_dicts,
+            target_duration=req.target_duration,
+            provider=req.provider,
+            model=req.model,
+            api_key=req.api_key,
+            base_url=req.base_url,
+        )
+        return result
+    except Exception as e:
+        logger.error(f"Clip creation failed: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.get("/ai/ollama-models")
+async def ollama_models(base_url: str = "http://localhost:11434"):
+    models = AIProvider.list_ollama_models(base_url)
+    return {"models": models}