Ross ROSS = Recommend OSS · open-source software intelligence for agents

LLM Wiki

Some data may be outdated — see provenance labels.

LLM Wiki is a cross-platform desktop application that turns your documents into an organized, interlinked knowledge base — automatically. Instead of traditional RAG (retrieve-and-answer from scratch every time), the LLM incrementally builds and maintains a persistent wiki from your sources。 observed · 2026-09-28

github.com/nashsu/llm_wiki · TypeScript · NOASSERTION (other) observed · 2026-09-28

Health v2 · maintenance only

76/100

  • Activity 97
  • Release rhythm 85
  • Longevity 13

Flags: no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.

  • gap_med: 1.0
  • age_days: 195
  • days_rel: 23
  • days_push: 23
  • n_releases_24m: 61

Full methodology

Adoption not part of the score

20016 stars · 2264 forks observed · 2026-09-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-10-19, confidence 0.97

LLM Wiki is a cross‑platform desktop application that automatically builds and maintains an interlinked knowledge base from your documents. It combines LLM‑driven ingestion, vector search, and graph analysis to keep the wiki current and searchable.

Use cases

  • organize my research papers into a searchable personal wiki
  • create an interlinked knowledge base from PDFs, Office files, and web clips
  • automatically ingest and index multimodal documents with LLM assistance
  • perform semantic search across all my personal documents using vector embeddings
  • maintain an up‑to‑date wiki of project documentation with automatic change detection

When to choose

  • you need a local, persistent knowledge base that grows incrementally
  • you want LLM‑powered document ingestion and source‑grounded retrieval
  • you require multimodal support for PDFs, images, and media
  • you value graph‑based insights and community detection on your data

When to avoid

  • you prefer a pure cloud‑only solution with no local installation
  • your hardware cannot run the Rust backend or Electron UI efficiently
  • you only need simple file storage without AI‑driven indexing

Facets

application · maturity active

gui agent-framework rag vector-database search-engine parser file-upload artificial-intelligence data-science windows cross-platform personal-knowledge-base incremental-wiki multimodal-ingest graph-insights deep-research rust-backend typescript-frontend linux macos electron desktop

1 source

Member repositories

RepositoryRoleHealth v2
nashsu/llm_wikimain76
nashsu/llm_wiki_skillplugin48

For agents

markdown · JSON · MCP: product_card(name="nashsu/llm_wiki")

Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem