contextgem VS sdk

As part of work on my open-source project ContextGem, I've built a native, zero-dependency DOCX converter that transforms Word documents into LLM-ready data.

This custom-built converter directly processes Word XML, provides comprehensive content extraction + covers what other open-source tools often miss or lack support for:

- Rich paragraph and sentence metadata for enhanced context

- Misaligned tables

- Comments, footnotes, and textboxes

- Embedded images

The converted document can then be easily used in ContextGem's LLM extraction workflows.

Perfect for developers building contract intelligence applications where precision matters. The converter preserves document structure and relationships, empowering LLMs to better understand and analyze document content.

Try it / share with your dev team today and see the difference in your document processing pipeline!

GitHub: https://github.com/shcherbak-ai/contextgem

All DocxConverter features: https://contextgem.dev/converters/docx.html

After getting tired of writing endless boilerplate to extract structured data from documents with LLMs, I built ContextGem - a free, open-source framework that makes this radically easier.

We created LightFeed to transform any websites into lightweight and focused news feed. Use LLM to sort and summarize posts using your own prompt. Feed is automated daily and you can receive it in browser, email or RSS. We are also shaping an enterprise plan that comes with 1000+ news sources already indexed and a real-time LLM query engine.

We will also open source the LLM web parser/sort library soon o (https://github.com/lightfeed/lightfeed). It reads HTML, turns main content into markdown, uses LLM to parse it into structured feed in JSON, then sort with embedding on user query. It is written in Typescript, uses llama index framework, and supports most LLMs on the market.

Any feedback is welcome!