AgenticRAG Survey

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Basic Information

This repository complements the survey paper on Agentic Retrieval-Augmented Generation (Agentic RAG) by providing a consolidated, researcher- and practitioner-focused resource about embedding autonomous agents into RAG pipelines. It documents foundational agentic patterns such as reflection, planning, tool use, and multi-agent collaboration, and presents a detailed taxonomy of Agentic RAG architectures including single-agent, multi-agent, hierarchical, corrective, adaptive, graph-based RAG and Agentic Document Workflows (ADW). The README contains comparative analyses contrasting Traditional RAG, Agentic RAG, and ADW, a catalogue of workflow patterns like prompt chaining, routing, parallelization, orchestrator-workers and evaluator-optimizer, and curated references and notebooks demonstrating practical implementations. The repo aims to help readers understand design trade-offs, real-world applications across domains such as healthcare, education, legal and finance, and directions for scalability, ethics, multimodal integration and human-agent collaboration.

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Features
Comprehensive taxonomy and patterns: clear definitions and diagrams for agentic patterns and workflow patterns including reflection, planning, tool use, multi-agent collaboration, prompt chaining, routing, parallelization and orchestrator-worker designs. Comparative analysis: side-by-side feature table contrasting Traditional RAG, Agentic RAG and ADW with strengths, weaknesses and best-fit scenarios. Practical implementations: annotated list of notebooks and example integrations using tools and libraries referenced in the README such as LangChain, LlamaIndex, LangGraph, Chroma, FAISS, Redis, Amazon Bedrock, AutoGen and Weaviate. Visual assets and workflows: architecture diagrams for single-agent, multi-agent, hierarchical and graph-based RAG and ADW diagrams. Applications and case studies: domain examples for healthcare, education, legal, finance, customer support and document-centric workflows. References and citation guidance for academic use.
Use Cases
The repository is useful as a reference and roadmap for designing, evaluating and implementing agentic RAG systems. It helps researchers and engineers choose appropriate architectures by explaining trade-offs among single-agent, multi-agent, hierarchical, corrective and adaptive approaches and by illustrating workflow patterns to optimize accuracy, latency and scalability. Practitioners gain hands-on starting points through curated notebooks and tool mappings showing common stacks and integrations for retrieval, vector stores and orchestration. The survey highlights real-world applications and domain-specific considerations for document workflows, multimodal reasoning and graph-based enhancements, and it summarizes challenges such as coordination complexity, ethical risks, privacy, scalability and human-agent collaboration to inform research agendas and deployment planning.

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