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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.

PyPI Version npm Version VS Code Marketplace Version Open VSX Version CI Status License

v9.9.0 Living Brain walkthrough

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 Brain Chat See how knowledge connects — a real relationship graph, not a file list Memory Graph
Capture anything — files, whole folders, notes, screenshots, web pages Capture Automate with review — agent changes become proposals you approve first Review Center
Pick a model in one click — recommended local models for your hardware Recommended Models Stay in control — audit, roles, retention in a separate admin surface Admin Console

Why Lattice AI

  • Own your memory — knowledge lives in a local SQLite Brain you can back up, export, inspect, and restore (.latticebrain encrypted 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:

Login Model install Model library

Screenshot index and capture notes: output/release/v9.9.0/SCREENSHOT_INDEX.md

Current Release

The current release is 9.9.0 — Fail-Closed Trust:

  • Change proposals can't clobber your edits. A proposal now records the original content hash; if the file changed before you approve, the apply is rejected with a conflict instead of silently overwriting your work, and the write is atomic. Duplicate/concurrent approvals apply exactly once.
  • A confused verifier never reports success. If the agent's critic output can't be parsed (after one strict retry), the run ends as NEEDS_REVIEW instead of a fabricated "done"; completion now requires a valid PASS and real execution evidence.
  • Every mutating tool is governed. A single-source inventory classifies each side-effecting tool; a CI gate fails closed if a new mutator ships ungoverned, and tools that would overwrite existing content without a reviewable proposal are blocked rather than applied.
  • Honest onboarding. Device analysis is modeled as loading | ready | unavailable; a failed probe no longer fabricates a "supported, ready on this computer" model card — it shows the cause, a retry, and "continue without a model."
  • Leaner & audited. Initial JS bundle is ~22% smaller (lazy-loaded heavy views, with a CI budget), plus dependency/SBOM audit and scheduled PostgreSQL integration workflows, a security-scan report, a model benchmark harness, and current/architecture documentation classification.

Release notes: RELEASE.md · Full history: docs/CHANGELOG.md

Expected artifacts for 9.9.0 release must use exact filenames:

  • dist/ltcai-9.9.0-py3-none-any.whl
  • dist/ltcai-9.9.0.tar.gz
  • ltcai-9.9.0.tgz
  • dist/ltcai-9.9.0.vsix
  • src-tauri/target/release/bundle/dmg/Lattice AI_9.9.0_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 9.9.0.
  • 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
9.9.0 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

License

MIT. See LICENSE.

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