XRPL AI

XRPL Chatbot Project

Problem Statement

Developers face challenges when building on the XRPL due to the complexity of understanding documentation. This project aims to improve the developer experience by providing an AI-powered chatbot that summarizes XRPL documentation, reducing the time needed to search and understand it.

Goals

• Create a chat-to-search bot for synthesized information in plain English text.
• Shorten the developer learning journey and educate on XRPL capabilities.
• Improve developer experience and increase XRPL adoption.

User Interaction

• The chatbot can be embedded on external websites, starting with xrpl.org.
• Existing Aloglia integration is kept and works alongside the new chatbot interface.
• End users can submit feedback about the quality of responses from within the chatbot UI.

Risks

• Potential social biases in responses.
• Security and data privacy concerns.
• Vulnerabilities and exploits.
• Denial of Service (DoS) attacks.
• Risk of incorrect or hallucinated responses.

Implementation and Rollout

The project has undergone private testing before rolling out to xrpl.org visitors. Ongoing monitoring, security testing, and improvements are planned.

Success Criteria

Success will be measured by user engagement, response accuracy, and performance metrics. External testing and user feedback will help maintain a high level of quality.

Further Investigations

Future work may involve exploring additional AI models and utilizing Transia's models as backends via JARVIS.