Clips AI: Python Library for AI Video Clip Generation

Clips AI is a developer-focused Python library built to solve a common content marketing headache: turning long, audio-driven videos into bite-sized clips for social media. Rather than relying on manual scrubbing and editing, Clips AI analyzes a video's transcript to intelligently pinpoint the most compelling moments, then packages them into ready-to-post clips. It's purpose-built for narrative, speech-heavy formats like podcasts, interviews, sermons, and webinars, where the spoken word carries the story. Beyond simply finding clips, Clips AI also handles the visual side of repurposing content. Its resizing algorithm dynamically reframes footage to keep the active speaker centered, automatically adapting videos into different aspect ratios suited for platforms like TikTok, Instagram Reels, or YouTube Shorts. Because it's delivered as a Python library rather than a polished SaaS app, it's aimed squarely at developers and technical teams who want to build automated, scalable clipping pipelines into their own workflows rather than click through a UI. By combining AI-driven transcript analysis with speaker-aware reframing, Clips AI helps content teams multiply their output from a single long-form recording. A single podcast episode or webinar can be broken down into dozens of clip candidates in a fraction of the time it would take a human editor, freeing creative teams to focus on strategy and distribution instead of manual trimming.

1. Install the Clips AI Python library into your development environment. 2. Transcribe your long-form video using WhisperX to generate an accurate transcript. 3. Run ClipFinder on the transcript to automatically detect and extract potential clip segments. 4. Use the resize function to reframe the chosen clips, supplying your Pyannote Hugging Face token to enable speaker diarization for accurate reframing. 5. Export the finished, platform-ready clips for publishing across your social channels.