DistillFeed: RSS reader with AI-ranked items and summaries (github.com)

DistillFeed is a newly launched RSS reader that leverages AI to rank items by relevance and generate concise summaries. The application supports both RSS and Atom feeds, allowing users to import and export OPML files. Its standout features include the use of OpenAI or local Ollama for scoring new entries and summarizing topics, as well as a plugin for generating daily digests from arXiv publications. Additionally, DistillFeed provides notification alerts with ntfy integration, enabling users to receive updates on selected articles via mobile devices. This development is significant for the AI/ML community as it exemplifies the growing trend of incorporating machine learning into content aggregation tools, enhancing the way users discover and interact with information. By utilizing AI for relevance scoring, DistillFeed aims to streamline information consumption, making it easier to filter through large volumes of content. The tool is designed for local use and supports Docker deployment, requiring Python 3.11 or newer. With features like customizable notifications, the separation of feed checking and AI processing, and budget-friendly operational safeguards, DistillFeed represents a thoughtful approach to improving user experience in RSS feed management.