Keywords
TEI, XML, React, AI Assistant, ODD

Technologies
React, Google Gemini AI, TEI XML, JavaScript, Vite

In the digital humanities, encoding historical manuscripts using the Text Encoding Initiative (TEI) XML standard is a notoriously steep learning curve for researchers. The objective of this project was to professionalize and drastically simplify this process by developing a modern, intelligent, and highly accessible TEI Annotation Web Application.

This project bridges the gap between historical text analysis and modern web technologies. The core deliverable is an interactive tagging environment that allows researchers to dynamically load custom ODD schemas and seamlessly apply complex TEI elements, attributes, and relationships directly to raw text without writing manual XML.

A unique and defining feature of this application is its integration with Google's Gemini AI. The system features a schema-aware AI Assistant that acts as an educational co-pilot. It automatically scans raw manuscript text to suggest contextually accurate TEI tags based strictly on the user's localized schema definitions, and provides real-time, plain-English validation and feedback on their XML structures. This radically lowers the technical barrier to entry for digital preservation.