ReelForge: Podcast Chapters and a Highlight Clip in One app.py

ReelForge is presented as a Pixeltable-based workflow for podcast and video episode processing that accepts MP4 or WAV files, generates Whisper transcripts, uses Gemini to create chapter metadata and identify a highlight segment, produces a clipped video and thumbnail, and indexes transcripts for semantic search. The example application defines a Podcasts table with media, metadata, derived audio, transcript, chapters, highlight assets, and an embedding index, then exposes routes for episode uploads and search through FastAPI. It argues that this unified, row-based approach can replace separate object storage, transcription jobs, LLM chaptering, FFmpeg processing, and vector-search services, while clarifying that it is not intended to replace editing software, publishing schedulers, CMS authentication, or frame-level visual search tools.

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