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STORM

Stanford's LLM-powered knowledge curation agent that researches any topic and generates a full Wikipedia-style article.

@ai-supply
Installationen78k
Bewertung★ 4.7
Rezensionen26
↗ Quell-Repository

STORM

STORM (Synthesis of Topic Outlines through Retrieval and Multi-perspective Question Asking) is a research agent from Stanford OVAL that turns any topic into a well-cited, Wikipedia-quality article. It uses a multi-agent perspective-guided research loop to gather diverse information before writing.

Key Features

  • Perspective-driven research: Identifies multiple expert viewpoints and generates questions from each angle to ensure comprehensive coverage
  • Multi-source retrieval: Searches the web (Bing, You.com, Tavily) and synthesizes information with citations
  • Outline-first writing: Generates a structured outline before writing to ensure logical flow
  • Co-STORM mode: Interactive, collaborative research session where a human and multiple AI agents research together in real time
  • Any LLM backend: Works with GPT-4, Claude, Gemini, Llama, and local models via LiteLLM
  • Citation grounding: Every claim in the output is linked to a source URL

Quick Start

pip install knowledge-storm
from knowledge_storm import STORMWikiRunnerArguments, STORMWikiRunner
from knowledge_storm.lm import OpenAIModel
from knowledge_storm.rm import YouRM

lm_configs = STORMWikiRunnerArguments(output_dir="./output")
runner = STORMWikiRunner(lm_configs, OpenAIModel("gpt-4o"), YouRM())
runner.run(
    topic="The impact of large language models on scientific research",
    do_research=True, do_generate_outline=True, do_generate_article=True
)

Add to ai-supply

npx ai-supply add storm-research-agent

Curated mirror of the open-source STORM (MIT). Get it from the source.

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