Looking for Feedback on "ScrapeSchema" – A Python Library for Extracting Entities & Relationships from Unstructured Data

Hey Indie Hackers! 👋

I’m excited to share ScrapeSchema, a oss Python library I’ve been working on, and I’d love to hear your thoughts and feedback!

What is ScrapeSchema?
ScrapeSchema is designed to extract entities and relationships from unstructured data (e.g., text files, web data, documents) and generate schemas that can help with:

Database structuring – creating meaningful tables from raw data.
Knowledge graphs – defining entities and relationships for advanced data insights.
Why I Built It:
During my projects, I faced challenges dealing with unstructured data, especially when trying to make sense of relationships between different entities. This led to the idea of ScrapeSchema – a tool to automate and simplify the process of understanding and organizing data.

Key Features:
Entity-relationship extraction from any text-based data source.
Schema generation that can easily integrate with databases or knowledge graph platforms.

What I’m Looking For:
I'm at an early stage and would love to get feedback from fellow developers, data enthusiasts, or anyone with experience in NLP and data modeling. Here are a few specific areas where your input would be invaluable:

Ease of use – Is the API intuitive enough for users?
Performance – Any speed or scaling issues when working with larger datasets?
Feature requests – What would make this tool more useful to you?
If this sounds interesting to you, please feel free to try it out and let me know your thoughts. I’d love to hear how I can make ScrapeSchema better and more useful!

Thanks in advance for any feedback or suggestions! 🚀