STORM tutorial: configurable research with a local LLM

This Russian-language video explains Stanford’s STORM research method and the speaker’s configuration of its repository. It contrasts simple query expansion with role-based searches and a dialogue between agents that ask follow-up questions. Parallel research branches gather material before the system combines their results into an article.

The speaker says users can supply an API key or connect a local model. Roles can be generated automatically or defined for a particular subject, with input and output token limits configured at each stage. The explanation covers removing duplicate URLs, comparing text embeddings for similar material, and writing individual sections with citations. This workflow searches the internet; the local model option does not make it an offline research tool.

The example includes a cited report, a separate Markdown expansion of basic concepts and a detailed activity log. The speaker identifies the Markdown expansion and log as personal additions. The closing advice is to adapt the research pipeline to a particular subject and use a configurable script when controlling token use matters.