SamyakJhaveri storm-research
Stanford's STORM (Synthesis of Topic Outlines through Retrieval and Multi-perspective question asking) — an LLM-powered research pipeline that produces Wikipedia-quality articles with citations.
Upstream: https://github.com/stanford-oval/storm
Install
pip install knowledge-storm
Usage with Claude
STORM has native Claude support via its ClaudeModel class:
from knowledge_storm import STORMWikiRunnerArguments, STORMWikiRunner
from knowledge_storm.lm import ClaudeModel
claude_model = ClaudeModel(
model="<your-model>", # e.g. claude-sonnet-4-6
max_tokens=4096
)
runner_args = STORMWikiRunnerArguments(
output_dir="./output"
)
runner = STORMWikiRunner(runner_args, claude_model, claude_model)
runner.run(
topic="Your Research Topic",
do_research=True,
do_generate_outline=True,
do_generate_article=True,
do_polish_article=True
)
API Keys Required
- ANTHROPIC_API_KEY — for Claude models
- Search engine key — one of: Bing, You.com, Serper, Brave, or Tavily
Co-STORM Mode
Co-STORM enables collaborative research where you and the LLM investigate together through multi-perspective questioning. Start a Co-STORM session to iteratively refine research direction.
How It Complements Loam
/researcher— quick web research, single-pass- STORM — systematic multi-perspective literature review with citations
Use /researcher for fast lookups. Use STORM when you need a structured article with proper citations.
Requirements
- Python 3.x
- dspy, litellm, streamlit
- Two API keys minimum (LLM + search engine)
Notes
- MIT license, Stanford-backed
- Development pace has slowed — may be less actively maintained
- No MCP server or Claude Code skill integration — requires Python invocation
- Best-in-class research quality for systematic reviews