Precis

screenshot of Precis
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Precis is an extensible self-hosted AI-enabled RSS reader with a focus on notifications and support for theming

Overview

If you’re on the lookout for a powerful RSS reader that integrates modern AI technologies, Précis may just be what you need. Pronounced "pray-see," this extensibility-oriented tool harnesses the capabilities of Large Language Models (LLMs) to summarize and synthesize content from various sources, ensuring that you are always in the know with timely notifications. With its hybrid storage options and customizable features, Précis aims to cater to both casual users and developers seeking flexibility in their information retrieval processes.

One standout aspect of Précis is its potential for integration. By supporting various LLM backends and notifications through popular platforms such as Slack and Jira, it allows users to adapt the application to fit their unique workflows. Whether you need quick updates on news articles or comprehensive summaries of lengthy reports, Précis is designed to streamline your information consumption.

Features

  • LLM Support: Leverage the power of Large Language Models like Ollama and OpenAI for summarizing content.

  • Notification Integration: Stay updated with timely notifications via platforms such as Slack, Jira, and ntfy.

  • Flexible Storage Options: Choose between embedded databases like tinydb or lmdb with the option for a hybrid storage handler for optimized performance.

  • Customizable Themes: Tailor the app's appearance to suit your personal style or brand preferences.

  • Null Handlers for Testing: Utilize null handlers for minimal functionality during testing phases or when notifications are not required.

  • Multi-instance Capability: Run multiple instances of Précis simultaneously by keeping storage and configuration separate through environment variables.

  • Development-Ready: Comes equipped with unit and integration tests, making it suitable for developers looking to contribute or customize further.

  • Deployment via Docker-Compose: The app can easily be deployed using Docker-Compose, simplifying the setup process for any user.

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Tailwind

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