Share this link via
Or copy link
Overview
“Modular RAGs” (Retrieval-Augmented Generation) refer to a flexible, component-based approach to building AI systems that combine retrieval mechanisms with generative models. Instead of relying on monolithic pipelines, Modular RAGs separate the core components—retriever, reader/generator, ranker, and orchestrator—allowing developers to customize and optimize each part independently based on task-specific requirements. In this architecture, the retriever fetches relevant documents or data chunks from a knowledge base, while the generator (typically a large language model) synthesizes responses using the retrieved context. Additional modules,...
Syllabus
- Implementing Modular Architectures for RAG Systems 16mins
Instructor
JS Padoan
Reviews
No reviews yet. Be the first to review!
Alternative Courses
This hands-on course introduces learners to Natural Language Processing (NLP)...
Free
You must be logged in to submit a review.