MindSearch: LLM-enhanced Search with Graph Theory and Multi-Agent

In my previous article, I introduced the core architecture, workflow, and implementation methods of LLM-enhanced search.

In this article, we'll explore MindSearch and provide insights.

Traditional search engines struggle to fully understand complex human queries.

Inspired by significant advances in LLMs, approaches that combine LLMs with search engines have gained popularity, such as the previously introduced Search with Lepton, which demonstrates a typical LLM-enhanced search workflow. However, these methods still face three key challenges:

• Search engines often cannot accurately retrieve all relevant information for complex queries in a single attempt.

• Useful information is scattered across multiple web pages mixed with considerable noise.

• A large number of web pages with long contents easily exceed LLMs' context window limits.

MindSearch is an LLM-based multi-agent framework that mimics human minds in web information seeking and integration.