Skip to main content

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

v9.8.0 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/v9.8.0/SCREENSHOT_INDEX.md

Current Release

The current release is 9.8.0 — Honest Knowledge Pipeline:

  • Every ingest (file, folder, web) now reports an extraction-quality score and warns on low-quality captures before they pollute the Brain.
  • Background folder ingestion is robust: per-item errors don't kill the job, progress (processed/total) is visible, and interrupted jobs resume — with a jobs API (/api/ingestion/jobs) and UI progress.
  • The Brain signals honestly: chat answers carry a context_quality marker when graph context is limited, and /api/brain/vector-freshness plus a UI banner show when knowledge is still waiting for vector indexing.
  • The agent evaluation gate grew to 16 deterministic scenarios, adding ingestion, concept-extraction, RAG-grounded answering, and automation proposal paths; automation suggestions gain confidence scoring and dedup.

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

Expected artifacts for 9.8.0 release must use exact filenames:

  • dist/ltcai-9.8.0-py3-none-any.whl
  • dist/ltcai-9.8.0.tar.gz
  • ltcai-9.8.0.tgz
  • dist/ltcai-9.8.0.vsix
  • src-tauri/target/release/bundle/dmg/Lattice AI_9.8.0_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 9.8.0.
  • 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; LLM-free simulation is labeled as such.

Release History

Version Theme
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.

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

ltcai-9.8.0.tar.gz (2.4 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ltcai-9.8.0-py3-none-any.whl (2.3 MB view details)

Uploaded Python 3

File details

Details for the file ltcai-9.8.0.tar.gz.

File metadata

  • Download URL: ltcai-9.8.0.tar.gz
  • Upload date:
  • Size: 2.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.5

File hashes

Hashes for ltcai-9.8.0.tar.gz
Algorithm Hash digest
SHA256 731bdb56dba9db47c93de0ffe8a8c67356022eda1bacbf0ed7b79e88a8be91f5
MD5 42ba198ec47e094ed1b700ab5218cc04
BLAKE2b-256 4d9b6f80c7cbebf65d52287067aedfb6998930ab494ad1d9c3601018442db73e

See more details on using hashes here.

File details

Details for the file ltcai-9.8.0-py3-none-any.whl.

File metadata

  • Download URL: ltcai-9.8.0-py3-none-any.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.5

File hashes

Hashes for ltcai-9.8.0-py3-none-any.whl
Algorithm Hash digest
SHA256 328ae734cb94fc0dedf18be3e9bce22a0cf8a05587f901d0fde48ab5adb3c1fb
MD5 ab83cd53b4d88e7c09da1e1d61c7e2e6
BLAKE2b-256 6104ea6af79917cb3bd5aaf65678062f708e1e9fed5bd5d98e9c5b9e8965c899

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page