Book rewrite (reduction of 40-60%) service with LLMs

I think LLMs are overused to summarise and underused to help us read deeper. I built a system for Claude Code to browse 100 non-fiction books and find interesting connections between them. I started out with a pipeline in stages, chaining together LLM calls to build up a context of the library. I was mainly getting back the insight that I was baking into the prompts, and the results weren't particularly surprising. On a whim, I gave CC access to my debug CLI tools and found that it wiped the floor with that approach. It gave actually interesting results and required very little orchestration…

Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…

Most book summaries on the internet are not detailed enough. In this project, I've tried to create detailed chapter-level summaries that retain a greater level of detail and vocabulary of the original. The aspiration is for these summaries to be a credible alternative to reading the books themselves. Website hosted on Vercel: https://book-summary-pro.vercel.app/ The code behind the project on GitHub: https://github.com/cosmic-glitch/book-summarizer Request additional books:…

I've developed a Python API service that uses GPT-4o for OCR on PDFs. It features parallel processing and batch handling for improved performance. Not only does it convert PDF to markdown, but it also describes the images within the PDF using captions like `[Image: This picture shows 4 people waving]`. In testing with NASA's Apollo 17 flight documents, it successfully converted complex, multi-oriented pages into well-structured Markdown. The project is open-source and available on GitHub. Feedback is welcome.

Hey HN! I'd love to get some people to mess around with a little side project I built to teach myself DSPy! I've been a big fan of reading fiction + webnovels for a while now, and have always been curious about two things: how can LLMs iteratively learn to write better based on reader feedback, and which LLMs are actually best at creative writing (research benchmarks are cool, but don't necessarily translate to real-world usage). That's exactly why I built narrator.sh! The platform takes in a user input for a novel idea, then generates serialized fiction chapter-by-chapter by using DSPy to…