Clips AI

Clips AI

Clips AI is an open-source Python library built for developers that automates long-form video clipping and resizing. Feed it podcasts, interviews, talks, or any narrative-driven footage and it intelligently splits the content into short, social-ready clips while dynamically switching aspect ratios—so creators can repurpose video at scale.
AI video clipping libraryopen-source Python video toolkitlong video to shorts converterauto resize video aspect ratiopodcast clip generatorvideo repurposing toolsmart video segmentationdeveloper video processing API

Features of Clips AI

Splits long videos into coherent shorts using AI-driven transcript segmentation
Auto-resizes footage: 16:9 → 9:16, 1:1, 4:5, or any custom ratio for TikTok, Reels, Shorts
WhisperX integration for word-level, time-stamped speech-to-text
Enhanced TextTiling + BERT embeddings detect semantic topic shifts for razor-sharp cut points
Speaker diarization, scene detection & face tracking reframe shots around the active speaker
Modular API: ClipFinder, MediaEditor, etc. plug straight into existing Python workflows
100 % open source—fork, extend, or embed in CMS, MAM, or serverless pipelines

Use Cases of Clips AI

Creators who need to turn hour-long podcasts or interviews into a batch of viral shorts
Marketing teams extracting highlight reels from webinars or product demos for paid ads
Developers adding server-side clipping & resizing to a custom CMS or automation stack
Social media managers bulk-converting landscape videos to portrait for TikTok, Reels, Shorts
Educators slicing lecture recordings into bite-size review clips for students
Editors speeding up post-production for speech-heavy content like sermons or keynote talks

FAQ about Clips AI

QWhat is Clips AI?

Clips AI is an open-source Python library that automatically cuts long, narrative videos (podcasts, interviews, talks) into short clips and resizes them for any social platform.

QWhat does Clips AI actually do?

It transcribes audio with WhisperX, finds semantic scene boundaries, splits the video into coherent segments, and re-crops each clip to the aspect ratio you need—portrait, square, or custom.

QWhich videos work best?

Speech-led, long-form content: podcasts, interviews, webinars, keynote speeches, sermons, lecture series—anything where the story is driven by dialogue.

QDo I need to code?

Yes. Clips AI is a developer tool; you install it via pip and call its Python API to automate clipping and resizing.

QHow does it decide where to cut?

WhisperX gives word-level timestamps; an improved TextTiling algorithm plus BERT embeddings spot topic shifts, creating natural cut points.

QIs Clips AI free?

The core library is open source and free to use. You only pay for optional cloud compute (e.g., GPU transcription) if you choose not to run models locally.

QCan it resize for every social network?

Absolutely—one command outputs 9:16 for TikTok/Reels, 1:1 for Instagram feed, 4:5 for Facebook, or any custom resolution.

QWhat tech powers it?

WhisperX (ASR), TextTiling + BERT (semantic segmentation), Pyannote (speaker diarization), PySceneDetect (scene cuts), MTCNN/MediaPipe (face detection).

QHow do I get started?

pip install clipsai, add FFmpeg & libmagic, grab a WhisperX model, then follow the quick-start notebook to transcribe, clip, and resize your first video.

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