Loreweave

A temporal knowledge engine for markdown vaults.
It indexes, links, remembers, forgets, and dreams — locally, over files you own.

Quickstart · What it does · CLI · Agent memory · Benchmarks · How it works · Research

Most knowledge tools are write-only. You capture diligently, the vault grows, and six months later you can't find the thing you know you wrote — because retrieval is keyword search over prose, nothing ever resurfaces on its own, and nothing notices when what you wrote last year stopped being true.

Loreweave is the layer that fixes that. Point it at a folder of markdown (Obsidian or plain) and it builds a knowledge graph, a bitemporal fact store, and a memory model over your notes — then hands them to you through a CLI and to your AI agents through MCP.

Three guarantees, enforced by the code rather than promised:

• Your files win. User markdown is never mutated; the engine only appends, and only under lore/. The vault is the source of truth — the index is a cache you can delete at any time and rebuild identically (there's a test for that).
• No LLM anywhere in the core. Indexing and retrieval use zero tokens and make zero network calls. Same vault, same query, same answer — forever.
• Memory you can read. Every fact an agent stores is a markdown line you can open, edit, and git diff.

Quickstart

npm i -g --allow-scripts=better-sqlite3 loreweave   # the flag is for npm 12: see Requirements
cd ~/my-vault
lore init          # creates .lore/
lore index         # incremental sync; one changed note: 32 ms at 1k notes, 656 ms at 20k (see Scale)

lore search "why did we drop the queue design"
lore ask "what's the status of project atlas"
lore dream         # what's duplicated, contradicted, stale, unlinked

Zero configuration and no network: out of the box it runs on BM25 + knowledge-graph spreading activation. Add local embeddings when you want them:

// .lore/config.json
{ "embedding": { "provider": "ollama", "model": "mxbai-embed-large" } }

Pick mxbai-embed-large (670 MB) for quality or nomic-embed-text (274 MB) when disk and indexing speed matter more — required task prefixes are applied automatically for both, and for the E5, BGE and Arctic families. The measured difference between the two is in Benchmarks. No embedding provider means lexical + graph retrieval, still fully functional.

Works with non-English vaults: Chinese, Japanese and Korean text is segmented per character so it is searchable at all, and other scripts index as written.

What it does

1. Knowledge that has a timeline. Facts are bitemporal: when they were true in the world (valid_from/valid_until) and when the system learned them (recorded_at). Contradictions supersede rather than overwrite, so history stays queryable.

$ lore assert "Ledger Format" status draft --valid-from 2026-01-01
$ lore assert "Ledger Format" status final --valid-from 2026-08-01
✓ Ledger Format :: status :: final
  supers

... [View full README on GitHub](https://github.com/lets-order-some-fries/loreweave#readme)