This AI edits videos with just a prompt! Lucy Edit tutorial
Semantic video editing tools like LucyEdit represent a major breakthrough for AI filmmakers wanting to modify existing shots without manual masking or rotoscoping.
What this lesson covers
This video explores LucyEdit by Decart, the first open-source semantic AI video editor that enables micro-editing on existing footage using text prompts. The creator demonstrates its capabilities in changing outfits, swapping characters, and adding objects while providing a tutorial on both online usage and local ComfyUI setup.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 00:20 ↗
LucyEdit is introduced as the first open-source semantic AI video editor developed by Decart for prompt-based video microediting.
- 01:40 ↗
Testing shows the model can accurately modify outfits and replace specific elements like clothing colors while preserving original poses and faces.
- 05:51 ↗
The online platform offers 2,000 free credits with a choice between a pro version and an open-source dev version.
- 07:04 ↗
Local installation is supported via a ComfyUI custom node repository for offline generation.
Workflow outlined in the video
- Access the online platform at platform.decart.ai to test LucyEdit with free credits.
- Clone the Lucy-Edit-ComfyUI repository into your local ComfyUI custom nodes folder for offline use.
- Upload an input video and craft specific natural language prompts to target desired changes like clothing color or object replacement.
- Select your preferred resolution (480p or 720p) and run the generation pipeline.
Before you use this workflow
These notes describe the source video at its publication date. Model access, pricing, connectors and interfaces may have changed. Check the original source and the provider’s current documentation before installing an add-on, connecting an account or spending credits.
ReelStack has not independently tested this workflow. Preview one representative shot and check motion, continuity and output quality before applying it to a full production. No result, cost saving or model capability is guaranteed.
Explore the tools
How to interpret the numbers
54,561 views captured 23 October 2026. ReelStack recommendation score: 19/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 45% performance: 0.29× views vs 6 other channel videos observed at a similar age. View-evidence factor 98% (views / (views + 1,000))
- 25% freshness: 0/100 with a 14-day half-life
- 20% momentum: 0 views/day vs 65 channel baseline (6 comparable uploads), with the same view-evidence factor
- 10% engagement: 86/100; likes + 4× comments, smoothed with a 500-view neutral prior