Multi-agent RAG Applications
Multi-agent retrieval-augmented generation system coordinating specialized agents for complex document-based question answering.
This system uses multiple specialized LLM agents that collaborate to answer complex questions across large document collections. Each agent handles a specific role: document retrieval, information extraction, reasoning, and response synthesis. Agents communicate via a shared message bus, enabling parallel processing and conflict resolution. Built on LangChain with support for multiple vector stores and LLM backends.