The app has comprehensive redaction review features to review and modify redactions. Also, fuzzy search through extracted text, identify duplicate pages in your documents or export to Adobe Acrobat to modify suggested redactions there. Github repo and user guide: github.com/seanpedrick-...

This augmented topics table is then presented to the LLM for the next batch, which grows iteratively as it progresses through the dataset. You can see the prompts used, and other settings on the LLM Settings tab. 7/7

You can also provide your own list of topics to the app that the LLM will assign to by default unless it finds novel topics (zero shot). The app uses Gemma 2B Instruct locally, or Google Gemini models / Claude models served on AWS via API. 3/7

Through judging sentiment and producing summaries for each topic, the app can pick up on more nuanced aspects of topics than 'traditional' topic modelling approaches based on clustering (such as the excellent BERTopic by @maartengr.bsky.social ). 2/7