33cca5f552
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
84 lines
2.4 KiB
Python
84 lines
2.4 KiB
Python
"""AI feature endpoints: filler word detection, clip creation, Ollama model listing."""
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import logging
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from typing import List, Optional
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from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel
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from services.ai_provider import AIProvider, detect_filler_words, create_clip_suggestion
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logger = logging.getLogger(__name__)
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router = APIRouter()
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class WordInfo(BaseModel):
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index: int
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word: str
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start: Optional[float] = None
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end: Optional[float] = None
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class FillerRequest(BaseModel):
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transcript: str
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words: List[WordInfo]
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provider: str = "ollama"
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model: Optional[str] = None
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api_key: Optional[str] = None
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base_url: Optional[str] = None
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custom_filler_words: Optional[str] = None
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class ClipRequest(BaseModel):
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transcript: str
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words: List[WordInfo]
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provider: str = "ollama"
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model: Optional[str] = None
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api_key: Optional[str] = None
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base_url: Optional[str] = None
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target_duration: int = 60
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@router.post("/ai/filler-removal")
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async def filler_removal(req: FillerRequest):
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try:
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words_dicts = [w.model_dump() for w in req.words]
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result = detect_filler_words(
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transcript=req.transcript,
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words=words_dicts,
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provider=req.provider,
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model=req.model,
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api_key=req.api_key,
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base_url=req.base_url,
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custom_filler_words=req.custom_filler_words,
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)
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return result
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except Exception as e:
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logger.error(f"Filler detection failed: {e}", exc_info=True)
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raise HTTPException(status_code=500, detail=str(e))
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@router.post("/ai/create-clip")
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async def create_clip(req: ClipRequest):
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try:
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words_dicts = [w.model_dump() for w in req.words]
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result = create_clip_suggestion(
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transcript=req.transcript,
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words=words_dicts,
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target_duration=req.target_duration,
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provider=req.provider,
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model=req.model,
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api_key=req.api_key,
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base_url=req.base_url,
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)
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return result
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except Exception as e:
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logger.error(f"Clip creation failed: {e}", exc_info=True)
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/ai/ollama-models")
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async def ollama_models(base_url: str = "http://localhost:11434"):
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models = AIProvider.list_ollama_models(base_url)
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return {"models": models}
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