Agentic RAG

4 Steps

1. 1

   Understand Basic RAG Limitations: Review the limitations of standard Retrieval-Augmented Generation (RAG) pipelines, such as their fixed retrieval process and inability to adapt to complex queries.

2. 2

   Implement a Query Planning Agent: Create an agent that analyzes the user query and breaks it down into sub-queries or determines the necessary tools for retrieval. Use LangChain or LlamaIndex agentic capabilities.

3. 3

   Build an Iterative Retrieval Loop: Design a loop where the LLM can decide whether to perform additional retrieval rounds based on the information gathered in previous steps. Use LangGraph to orchestrate the loop.

4. 4

   Integrate Tools for Augmented RAG: Extend the agent's capabilities by integrating tools beyond basic retrieval, such as calculators, web search, or database access. Use LlamaIndex Workflows to manage tool orchestration.