Lattice AI — local-first Digital Brain that keeps your knowledge durable across any AI model.
Project description
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. Any model — local MLX or cloud — can speak with that memory. Nothing leaves your machine without explicit consent.
대화·파일·폴더·웹페이지가 전부 내 컴퓨터 안의 지식 그래프로 쌓이고, 어떤 모델이든 그 기억을 이어받아 대화합니다.
What You Can Do
| 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 |
Stay in control — audit, roles, retention in a separate admin surface |
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.
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:
Screenshot index and capture notes: output/release/v9.9.4/SCREENSHOT_INDEX.md
Current Release
The current release is 9.9.4 — Durable Loops:
- Loops that survive restarts. Paused
awaiting_approvalruns are persisted to disk (hashed tokens, wall-clock expiry) and resume after a server restart; expired approvals answer with a one-click replan hint, andGET /agent/approvalsre-surfaces pending runs. Approval cards show a live TTL countdown. - You can watch the loop work. Streamed agent runs emit named
agent_stepSSE events (plan → tools → verify → terminal) rendered as a live step timeline; weak-model parse repairs are counted and surfaced honestly ("모델 응답을 N회 보정했어요"). - One retrieval policy. A single
RetrievalPolicymodule (rule-based query rewrite, query-class weights, 14-day recency age-decay in a [0.5, 1.0] band) feeds both the service and graph fusion layers, gated by the benchmark CI test; embedder swaps now reportstale_embedderinstead of silently emptying the vector channel. - Retrieval quality at the chunk level. Markdown chunks at heading
boundaries (with
heading_pathprovenance), code at function boundaries, PDF chunks carry page numbers, plain text stays byte-identical — and cited source cards click through to the stored chunk text. - Grounded answers, cited sources. When retrieved context exists the answer prompt instructs [1]-style citations; a synthetic grounding bench gates the verdict heuristic in CI; briefings suggest periodic graph noise curation, and an opt-in review mode stages curator promotions for human approval.
- A wider harness. Manifest-aware plan rewriting plus React/Vite and Python-package manifests, a bounded executor context window, five deterministic workflow scenarios, a funnel soft gate, and a weekly fail-open real-model agent smoke with a report artifact.
Release notes: RELEASE.md · Full history: docs/CHANGELOG.md
Expected artifacts for 9.9.4 release must use exact filenames:
dist/ltcai-9.9.4-py3-none-any.whldist/ltcai-9.9.4.tar.gzltcai-9.9.4.tgzdist/ltcai-9.9.4.vsixsrc-tauri/target/release/bundle/dmg/Lattice AI_9.9.4_aarch64.dmg
Do not use wildcard artifact uploads. Package registry publishing remains owner-run.
Architecture At A Glance
FastAPI on localhost is the source of truth; the React/Vite frontend and the
Tauri desktop shell sit on top; the independent lattice_brain package owns
the graph, memory, ingestion, and portability. Local-first by default — cloud
calls, downloads, Telegram, and update checks are opt-in.
See ARCHITECTURE.md for details and
docs/DEVELOPMENT.md for the developer workflow
(npm install && npm run dev, 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.
- PostgreSQL/pgvector is optional scale/migration tooling. SQLite remains the live local Brain store in 9.9.4.
- Docker, model downloads, cloud model calls, Telegram, Brain Network, and update checks require explicit user action.
- 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.
Release History
| Version | Theme |
|---|---|
| 9.9.4 | Durable Loops |
| 9.9.3 | Closed Loops |
| 9.9.2 | Artifact Trust |
| 9.9.1 | Clean Foundations |
| 9.9.0 | Fail-Closed Trust |
| 9.8.0 | Honest Knowledge Pipeline |
| 9.7.0 | Proactive Hybrid Brain |
| 9.6.0 | Trusted Agent Loop |
| 9.5.0 | Command Center |
| 9.4.0 | Question-Driven Everyday Automation |
| 9.3.0 | Proactive Brain Intelligence |
| 9.2.0 | Model-Agnostic File Generation |
| 9.1.0 | Code Review Completion & Fail-Closed Runtime |
| 9.0.0 | Code Review Closure & Runtime Cleanup |
| 8.9.0 | Scoped Memory & Tool Policy Hardening |
| 8.8.0 | Brain Core Extraction & Recall Proof Hardening |
| 8.7.0 | Runtime State Hygiene & Release Evidence Refresh |
| 8.6.0 | Desktop Capture & Navigation Reliability |
| 8.5.0 | Tool Registry Readiness & Config DI |
| 8.4.0 | Action-Aware Brain Chat |
| 8.3.0 | Orchestrated Brain Readiness |
| 8.2.0 | Brain Brief |
| 8.1.0 | Intuitive Brain Home |
| 8.0.0 | Runtime Architecture Contract |
Per-release details: RELEASE_NOTES.md
Documentation
- docs/WHY_LATTICE.md — product philosophy
- docs/TRUST_MODEL.md — local-first trust model
- PRIVACY.md — privacy and external communication policy
- FEATURE_STATUS.md — feature status and limitations
- SECURITY.md — security posture
- RELEASE.md — release guide and notes
License
MIT. See LICENSE.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file ltcai-9.9.4.tar.gz.
File metadata
- Download URL: ltcai-9.9.4.tar.gz
- Upload date:
- Size: 2.5 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.14.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
995d277973d1d2e38cb0f4b93f678a0dae401cbdefcbfc96f518d1c46d3ac3c0
|
|
| MD5 |
4b5ce071e38ee69ba36946a4686c32d1
|
|
| BLAKE2b-256 |
e4d8e29e85e25d61d4d390c5c34c12e9dfc513f2d8f4a2c66060b7f4c0157035
|
File details
Details for the file ltcai-9.9.4-py3-none-any.whl.
File metadata
- Download URL: ltcai-9.9.4-py3-none-any.whl
- Upload date:
- Size: 2.4 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.14.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
7644b1869e794916fe98175792d53e66ba47833a5042ba280cca03f4d50dace2
|
|
| MD5 |
a24c7f93e668f57641294e5fcb312440
|
|
| BLAKE2b-256 |
b6ed527a7479a580b8068c226c7b21149b232dd829642d8a772cd2d7a5807fc4
|