contextgem VS llm-client-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.

That’s where llm-client and LangChain come into play. These LLM integration tools provide a streamlined approach to incorporating different language models into your projects. They simplify the integration process, abstracting away the complexities and nuances associated with each individual LLM. With llm-client and LangChain, you can save valuable time and effort that would otherwise be spent on understanding and integrating multiple LLMs.