AgriIR Framework Introduces Modular RAG System for Domain-Specific Knowledge Retrieval

A novel framework for configurable retrieval augmented generation, named AgriIR, has been unveiled to deliver domain-specific, grounded responses efficiently and with minimal computational expense. This system breaks down information retrieval into modular stages, including query refinement, sub-query planning, retrieval, synthesis, and evaluation. Such a design enables users to adjust the framework for various knowledge areas without altering its fundamental architecture. Specifically aimed at Indian agricultural information retrieval, the reference implementation combines 1B-parameter language models with adaptive retrievers and domain-specific agent catalogs. AgriIR promotes deterministic citation methods and incorporates telemetry for enhanced operational clarity. It includes automated deployment tools to ensure operations are auditable and reproducible. The framework prioritizes modular control and architectural design over reliance on large, monolithic models. The paper describing this framework was published on arXiv under the identifier 2604.16353v1 and is classified as a cross announcement type.