stanford-oval/storm
storm
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
Overview
An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
Best for
- Evaluating storm for Python AI workflows.
- Comparing a GitHub project with 28,244 stars and current repository activity.
Pros
- storm has visible GitHub traction with 28,244 stars. Topics: agentic-rag, deep-research, emnlp2024.
- The project provides an external homepage for deeper evaluation.
Cons
- Production fit still depends on documentation depth, issue activity, and release cadence.
- License review should confirm the MIT terms fit your use case.
Production readiness
storm should be validated with its README, release history, open issues, and integration requirements before production use.
License risk
MIT is reported by GitHub; review the repository license before redistribution or commercial use.
Install
git clone https://github.com/stanford-oval/storm.gitconda create -n storm python=3.11conda activate stormpip install -r requirements.txtpip install knowledge-storm