Skip to content

RAG Context Enrichment 💎

Supported Git Platforms: GitHub

Overview

What is RAG Context Enrichment?

A feature that enhances AI analysis by retrieving and referencing relevant code patterns from your project, enabling context-aware insights during code reviews.

How does RAG Context Enrichment work?

Using Retrieval-Augmented Generation (RAG), it searches your configured repositories for contextually relevant code segments, enriching pull request (PR) insights and accelerating review accuracy.

Getting started

Prerequisites

  • Database setup and codebase indexing must be completed before proceeding. Contact support for assistance.

Configuration options

In order to enable the RAG feature, add the following lines to your configuration file: 

[rag_arguments]
enable_rag=true

RAG Arguments Options

enable_rag If set to true, repository enrichment using RAG will be enabled. Default is false.
rag_repo_list A list of repositories that will be used by the semantic search for RAG. Use ['all'] to consider the entire codebase or a select list of repositories, for example: ['my-org/my-repo', ...]. Default: the repository from which the PR was opened.

References from the repository will be shown in a collapsible bookmark, allowing you to easily access relevant code snippets:

References

Limitations

Querying the codebase presents significant challenges

  • Search Method: RAG uses natural language queries to find semantically relevant code sections
  • Result Quality: No guarantee that RAG results will be useful for all queries
  • Scope Recommendation: To reduce noise, focus on the PR repository rather than searching across multiple repositories

This feature has several requirements and restrictions

  • Codebase: Must be properly indexed for search functionality
  • Security: Requires secure and private indexed codebase implementation
  • Deployment: Only available for Qodo Merge Enterprise plan using single tenant or on-premises setup
Footer