unstract

The primary challenge is not just about harnessing AI for search; it's about preparing complex documents of various formats, structures, designs, scans, multi-layout tables, and even poorly captured images for LLM consumption. This is a crucial issue. There is a 20 min read on why parsing PDFs is hell: https://unstract.com/blog/pdf-hell-and-practical-rag-applica... To parse PDFs for RAG applications, you'll need tools like LLMwhisperer[1] or unstructured.io[2]. Now back to your problem: This solution might be an overkill for your requirement, but you can try the following: To set things up quickly, try Unstract[3], an open-source document processing tool. You can set this up and bring your own LLM models; it also supports local models. It has a GUI to write prompts to get insights from your documents.[4] [1] https://unstract.com/llmwhisp

Hey HN! Over the last few months, we’ve seen many tools here trying to tackle the problem of making complex, unstructured documents ready for LLMs. The complexity primarily includes parsing highly complex documents in terms of format, layout, design, complex tables, checkboxes, etc, with high accuracy and reliability. LLMWhisperer is our take on the problem. LLMwhisperer solves most of the document complexity with reliable accuracy. We offer a generous Free Forever plan that allows processing 100 pages/day. With our user-friendly playground (https://pg.llmwhisperer.unstract.com/), you can effortlessly test your document use case. No sign-up is required. We eagerly await your valuable feedback. LLMWhisperer is also a part of Unstract, an open-source document processing automation platform. Links: https://llmwhisperer.unstract.com/ Playgrou