Enhance README with AI/RAG Implementation Guidance#130
Open
HiteshSingh21 wants to merge 1 commit into
Open
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
This PR adds a section to the README.md about machine-readability and LLM integration.
As genomic data compliance tools move toward automated verification (e.g., the RegBot project), developers need clearer guidance on connecting traditional semantic logic with modern RAG-based pipelines.
Changes Included -
• Vector Search & DAG Warning
Explains how DUO’s Directed Acyclic Graph (DAG) hierarchy should be resolved before using vector databases, to avoid incorrect similarity calculations.
• Flat File Indexing
Recommends using the lightweight duo.csv file for system prompts and vector indexing instead of the heavier .owl ontology files.
Justification (Governance Alignment) -
• Simplicity – Points developers to the most practical files for NLP and indexing.
• Machine-readability – Helps automated tools interpret DUO constraints without requiring manual ontology parsing.
Contributor:
Hitesh Singh (GSoC '26 Applicant)