Verified project record

stanford-oval/storm

STORM automates the research and writing process to generate long, Wikipedia-style articles with citations from scratch. It uses multi-perspective question asking and simulated conversations with topic experts grounded in Internet sources to curate knowledge before writing.

Project overview

Project type: AI Agent · RAG · Workflow
Use cases: Documents & Office · Search & Research
Deployment: Python environment
License: MIT

Best for

Researchers, developers, and general users needing an automated pipeline to curate knowledge and generate long-form content with citations.
Users who require customization of language models, retrieval integrations, and pipeline modules for their specific research workflows.

Key capabilities

Breaks down generating long articles with citations into pre-writing research and writing stages to produce a full-length article.
Discovers different perspectives by surveying existing articles from similar topics and uses them to control the question-asking process to improve research depth.
Simulates a conversation between a writer and a topic expert grounded in Internet sources to update understanding and ask follow-up questions.
Implements a turn management policy to support collaboration among LLM experts, a Moderator, and human users to steer the discussion.
Maintains a dynamic updated mind map to organize collected information into a hierarchical concept structure and build a shared conceptual space between the human user and the system.
Provides a modular engine interface allowing customization of different language models, retrieval integrations, and pipeline modules.
Supporting user participation in the knowledge curation process.
Developing abstractions for curated information to support presentation formats beyond the Wikipedia-style report.

Limitations and risks

The system cannot produce publication-ready articles that often require a significant number of edits.

Getting started

Install the knowledge-storm library via pip. Configuring external API keys for language models and search engines in secrets.toml is required. Running a Python script is the first success path for STORM or Co-STORM.

Evidence and sources

GitHub project description: An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
README: We add [litellm](https://github.com/BerriAI/litellm) integration for language models and embedding models in `knowledge-storm` v1.1.0.
README: While the system cannot produce publication-ready articles that often require a significant number of edits, experienced Wikipedia editors have found it helpful in their pre-writi…
README: STORM breaks down generating long articles with citations into two steps: 1. **Pre-writing stage**: The system conducts Internet-based research to collect references and generates…
README: Co-STORM codebase is now released and integrated into `knowledge-storm` python package v1.0.0. Run `pip install knowledge-storm --upgrade` to check it out.

Reviewed at: 2026-07-17T10:03:08Z