Controllable RAG Agent for complex tasks that require reasoning

RAG (Retrieval-Augmented Generation) is a method that combines the power of LLMs with your own data to enrich the LLM's knowledge with external information.

While there are many ways to build a RAG system and challenges to address in the process, an even greater challenge arises when answering questions that require reasoning, such as:

"What caused the protagonist of the plot to defeat the villain's assistant?"

To tackle this, I created an agent that facilitates this reasoning process and integrated it with a RAG system.

In my blog post, I provide a full explanation, including the code and a video lecture where I delve into the details.

Link to the full blog post: https://open.substack.com/pub/diamantai/p/controllable-agent-for-complex-rag?r=336pe4&utm_campaign=post&utm_medium=web&showWelcomeOnShare=false

feel free to ask anything about it :)