Lattice AI
Your model is the voice you use today. Your Brain is the asset you keep.
모델은 갈아타도, 내 지식은 내 컴퓨터에 남는 로컬 우선 AI 브레인.
Chat, files, folders, notes, and web pages all flow into one durable knowledge
graph on your computer. The default is local. Cloud is optional — an
OAuth-authenticated CLI (agy / grok) or an API key you configure — and
nothing leaves your machine without explicit consent.
대화·파일·폴더·웹페이지가 전부 내 컴퓨터 안의 지식 그래프로 쌓입니다. 기본은 로컬이고, 클라우드는 선택입니다 (OAuth CLI 지원).
What You Can Do
See your Brain's story in time — a growth curve, an activity heatmap, and each day's story, rewindable to any past moment  |
Chat with a Brain that remembers — every conversation grows durable, source-linked memory  |
See how knowledge connects — a real relationship graph, not a file list  |
Capture anything — files, whole folders, notes, screenshots, web pages  |
Automate with review — agent changes become proposals you approve first  |
Pick a model in one click — recommended local models for your hardware  |
Watch a file become memory — three named steps, not a pipeline diagram  |
Say how much it may do alone — one dial in plain words; dangerous actions stay blocked either way  |
Why Lattice AI
- Own your memory — knowledge lives in a local SQLite Brain you can back up,
export, inspect, and restore (
.latticebrainencrypted archive). - Model-independent — switch between local MLX models and cloud models without rebuilding context from zero.
- Honest by design — the Brain tells you when retrieval context is limited, when captured pages extracted poorly, and when the vector index is catching up.
- Safe automation — automations are consent-first drafts; edits to existing content always pass through a reviewable proposal with a diff.
- Runs on the model your machine can hold — the loop measures what a model can actually produce and adapts: a model too small to emit a tool call is walked through numbered choices instead, with the same permission gates, snapshots and sanitizers as every other profile.
매번 AI에게 프로젝트 맥락을 다시 설명하고 있다면, 지식이 여러 서비스에 흩어져 있다면, 그 기억을 특정 회사가 아니라 내가 소유하고 싶다면 — Lattice AI가 그 브레인입니다.
Quick Start
pip install ltcai # or: npm install -g ltcai
LTCAI # then open http://127.0.0.1:4825/app
Apple Silicon local models: pip install "ltcai[local]". Desktop app (Tauri)
ships as a dmg on each GitHub Release.
First-run flow — wake the Brain, pick the owner, load a recommended model:
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 |
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Screenshot index and capture notes: output/release/v12.0.0/SCREENSHOT_INDEX.md
Current Release
The current release is 12.0.0 — Open House:
11.9.0 made the doors answer. This release opens the house: the two
largest crates are grouped by what a file is for, the contributor
documentation is a real path in, and four gaps the last release wrote
down are closed. lattice-host serves 422 operations across 41 route
families (POST /mcp and the folder-prune route are the two new ones),
and the AI worker is 20 routes (POST /worker/vector/query is the
one addition). Cloud is still optional and the default is still local.
- Complexity management first.
lattice-agentis six groups —kernel(the loop and every decision that can refuse),parse,content,tools,surface,prompts— andlattice-platformis seven domains. Every move is a rename, so the goldens answer identically; each crate carries its ownARCHITECTURE.md, anddocs/DEVELOPMENT.mdand the newdocs/ROADMAP.mdare the way in. - Small models become agents. A measured probe (not a size regex)
picks the profile, and the
guidedprofile stops asking for JSON at all: pick an action by number, then one argument per turn, and the harness assembles the call. A 0.5B model finished a real file in 3.9s. The same gates, snapshots and sanitizers run on every profile. - Remembering got faster and more careful. Re-indexing an unchanged folder went 33s → 0.26s, a 991-item embedding backlog went 40 minutes → 15.3s, and a document's own section outline is now in the graph, so an answer can name the heading it came from. Korean queries strip their particles properly, and deleted files get a 「삭제된 파일 정리」 button instead of quietly lingering as memory.
- Four honest gaps closed. Restore takes effect without a restart,
/setup/installreally installs on per-item consent,POST /mcpis inside the OpenAPI contract, and pointer tools are declared aspip install "ltcai[pointer]".
What this release does not close — small-model content quality, the
mock-only api_key path, brute still being the search default, watch
never deleting on its own, the ad-hoc-signed dmg — is listed in
RELEASE_NOTES_v12.0.0.md.
Expected artifacts for 12.0.0 release must use exact filenames:
dist/ltcai-12.0.0-py3-none-any.whldist/ltcai-12.0.0.tar.gzltcai-12.0.0.tgzdist/ltcai-12.0.0.vsixsrc-tauri/target/release/bundle/dmg/Lattice AI_12.0.0_aarch64.dmg
Do not use wildcard artifact uploads. Package registry publishing remains owner-run.
Release notes: RELEASE.md · Full history: docs/CHANGELOG.md
Architecture At A Glance
One Rust server on localhost is the source of truth: lattice-host answers
every product route, owns every write to the Brain, and supervises a Python
AI worker it reaches over loopback for the things a model does — inference,
embedding, extraction, parsing, rendering, speech-to-text. The React/Vite
frontend and the Tauri desktop shell sit on top of that one door. Local-first
by default — cloud is optional (OAuth CLI or an API key you configure),
and downloads, Brain Network, and update checks are opt-in.
See ARCHITECTURE.md for details and
docs/DEVELOPMENT.md for the developer workflow
(npm start / bin/ltcai.js is the product; npm run dev is the
20-route worker). Each of the two largest crates carries its own domain
map — rust/lattice-agent/ARCHITECTURE.md
and rust/lattice-platform/ARCHITECTURE.md
— and open gaps are tracked in docs/ROADMAP.md.
Validation via npm run lint, npm run test:unit, npm run test:visual.
Known Limitations
- External package registries are owner-published and can lag behind GitHub.
- SQLite is the live local Brain store. The optional PostgreSQL/pgvector migration tooling is not part of the 12.0.0 worker.
- Docker, model downloads, cloud model calls, Brain Network, and update checks
require explicit user action. Cloud is optional:
cli_oauth(agy/grok) was live-checked at zero billing; theapi_keypath is mock-verified only. - The Telegram bridge was removed in 11.6.0 — it lived in the platform code that became the AI worker. SSO/OIDC login and callback flows were removed with it; the configuration surface remains and password login is native.
- Conversation does not fabricate answers when no model is loaded. Agent and workflow simulation without a loaded LLM is deterministic and LLM-free (it does not call a model) — labeled as such, never presented as autonomous model success.
POST /worker/render/pdfships working out of the box:reportlabis a required dependency as of 11.6.0 (it used to be an undeclared lazy import that raised a 500;ltcai[pdf]remains as an empty alias for older install instructions).- The multimodal image and video analysis functions have no HTTP door as of 11.8.0: their only route wrapped a native image ingest that was never built. The observation code stays in Brain Core under unit test, and its module header says so.
- The Python coverage gate is a line floor of 90 since 11.8.0 (the 100%-lines-and-branches gate was removed). The enforced claim is the floor, not whatever a given run measures.
- Small-model content quality is gated honestly. With the
guidedprofile even a 0.5B model writes the requested file and reaches DONE; a weak summary still fails the critic and the run ends FAILED/NEEDS_REVIEW rather than claiming success. - Vector search still defaults to
brute— exact and byte-compatible.hnsw+rescoreis real but opt-in, and falls back to the exact scan with its reason when the sidecar cannot answer. - Watch never deletes on its own: a vanished file is reported, and cleanup runs only through the confirmed folder-prune flow.
- The macOS dmg is ad-hoc signed — effectively unsigned — so first launch needs the usual Gatekeeper step.
- Pointer-control tools execute in the worker and are installed with
pip install "ltcai[pointer]". Remaining honest gaps (open_keyspending-only, no Self-Model refiner,delete_nodeleavingPART_OF, review events silent without an owner, KG-api ingest text-only, two store cycles per review mutation) are listed with their reasons in RELEASE_NOTES_v12.0.0.md and prioritized in docs/ROADMAP.md.
Release History
Public history starts at 11.0.0. 11.6.0 rebuilt the product server in Rust and
reduced the Python package to an AI worker, so a 10.x or 9.x install is a
different program; SECURITY.md supports only 11.x, and this table states the
same boundary. Earlier notes stay in the tree as RELEASE_NOTES_v*.md files.
| Version | Theme |
|---|---|
| 12.0.0 | Open House |
| 11.9.0 | Working Order |
| 11.8.0 | Travel Light |
| 11.7.0 | Clean Sweep |
| 11.6.0 | One Door |
| 11.5.2 | Tight Ship |
| 11.5.1 | Rust Full Loop |
| 11.5.0 | Rust Complete |
| 11.4.0 | Rust Foundation |
| 11.3.0 | Time Remembers |
| 11.2.0 | All Systems On |
| 11.1.0 | Product Intelligence |
| 11.0.1 | Both Branches |
| 11.0.0 | Full Measure |
Per-release details: RELEASE_NOTES.md
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