ltcai 3.1.0

Lattice AI v3 local-first AI workspace platform with knowledge graph, vector index, hybrid search, agents, and workspace modes

Lattice AI

Lattice AI v3 — Local-First AI Workspace Platform.

Work across Personal and Organization workspaces with Knowledge Graph, Vector Index, Hybrid Search, Native Chat, agents, files, models, and Basic / Advanced / Admin modes.

Install

Install the local workspace:

pip install ltcai

Add Apple Silicon local model support:

pip install "ltcai[local]"

Install the npm CLI:

npm install -g ltcai

Install the coding extension:

• VS Code Marketplace: parktaesoo.ltcai
• Open VSX: parktaesoo.ltcai
• GitHub Release v3.1.0

Quick Start

Start the workspace:

LTCAI

Then open:

http://127.0.0.1:4825/app

Development checkout:

npm install
npm run dev

Useful validation commands:

npm run check:python
npm run test:unit
npm run build

What Is Lattice AI?

Lattice AI v3 is a local-first AI workspace platform for people and teams who want their files, models, graph context, retrieval, and agent workflows in one place.

• Primary app shell: /app is the default product experience with Native Chat, Knowledge Graph, Hybrid Search, Files, Pipeline, Agents, Models, My Computer, Settings, and Admin areas. Classic pages remain compatibility routes only; normal workflows stay in /app.
• Local-first AI Workspace: work starts on your machine, with local data and workspace state by default.
• AI Pipeline Platform: plan, execute, review, retry, and replay work across local models, cloud models, tools, files, and generated artifacts.
• Knowledge Graph Platform: documents, images, screenshots, notes, conversations, and decisions become linked entities, relationships, evidence, and reusable context.
• Multi-Agent Workflow Platform: agents hand off structured context, review work, retry with reasons, and keep timelines inspectable.
• Personal / Organization Workspace: move between personal work and team workspaces with role-aware views and Basic / Advanced / Admin modes.
• Vector Index and Hybrid Search: local vector rows are derived from the Knowledge Graph and fused with keyword and graph signals.
• Local Model Management: choose current multimodal local models with source disclosure, hardware-aware recommendations, and cloud fallback options.
• Community-first workspaces: Personal and Organization workspaces ship in the local product; enterprise SSO/SCIM/governance remain future extensions.

Why Lattice AI?

Most AI tools split your work across a chat window, a model picker, loose files, and disconnected automations. Lattice AI keeps those parts together:

• files and conversations become graph context;
• graph context feeds pipelines and coding actions;
• model cards disclose country, company, run mode, internet usage, and model identity;
• personal and organization workspaces keep team workflows separate from local work;
• multi-agent workflows leave behind replayable plans, reviews, retries, and outcomes.

v3.1.0 Highlights

Lattice AI v3.1.0 completes the non-enterprise local-first workspace platform around /app: Classic is retired from normal workflows, retrieval is wired through a shared service layer, and browser assets are hash-manifested.

• Native v3 Chat lives inside /app#/chat and streams through the real POST /chat backend while showing friendly setup guidance when no model is loaded.
• Knowledge Graph, Vector Index, and Hybrid Search are first-class retrieval surfaces. Hybrid results show keyword, local vector, and graph scores.
• Personal and Organization workspaces, plus Basic / Advanced / Admin modes, are built into the shell.
• Models can load/unload from the native Models view; Agents read the AgentRuntime boundary with run health, history, events, replay, and stop affordances.
• Production embedding profiles cover local bge-m3, nomic-embed-text, e5-large, gte-large, Ollama nomic-embed-text, mxbai-embed-large, BGE-M3-compatible providers, MLX, and OpenAI-compatible text-embedding-3-small / text-embedding-3-large. Hash embeddings remain fallback only.
• /app loads static/v3/asset-manifest.json and build-generated hashed assets such as app.<hash>.js and lattice.base.<hash>.css; manual ?v= cache-busting is no longer used by runtime HTML.

Screenshots

Workspace

Knowledge Graph

AI Pipeline

Admin Dashboard

Mobile Responsive

Knowledge Graph Flow

files / documents / images / screenshots / conversations / decisions
  -> multimodal understanding
  -> entity and relationship extraction
  -> evidence and artifact storage
  -> Knowledge Graph update
  -> AI pipeline context
  -> coding actions / analysis / documents / team workflows

The graph keeps useful workspace context available even when you change models.

v3 Backend Retrieval

The v3 backend adds a local-first retrieval stack that combines the Knowledge Graph, a SQLite vector index, and hybrid result fusion. It preserves existing graph data while adding derived vector rows that can be rebuilt at any time.

Embedding status: production profiles are exposed through GET /api/embeddings/providers, while lattice-local-hash-v1 remains a deterministic fallback for offline indexing and tests. It is never presented as a production semantic embedding model.

Core API contracts:

• POST /api/search/hybrid
• GET /api/search/keyword?q=...
• GET /api/search/vector?q=...
• GET /api/graph
• GET /api/graph/node?node_id=...
• GET /api/graph/relationship
• GET /api/index/status
• POST /api/index/rebuild

See docs/V3_BACKEND_ARCHITECTURE.md for the storage model, search model, migration behavior, and API response shape.

Local Model Policy

Lattice AI recommends current-generation multimodal models for local use and keeps local model choices explicit.

Family	Default role	Example recommendation
Gemma 4	Default Google multimodal family	mlx-community/gemma-4-12b-it-4bit
Gemma 4 large	Higher-quality local multimodal work	mlx-community/gemma-4-31b-it-4bit
Qwen3-VL	Smaller, balanced multimodal options	mlx-community/Qwen3-VL-4B-Instruct-4bit
Llama 4	Meta multimodal option	mlx-community/Llama-4-Scout-17B-16E-Instruct-4bit

Every recommended model card shows maker country, maker company, run mode, internet requirement, and model name. See MODEL_POLICY.md.

Architecture

Personal / Organization Workspace
  -> files, chats, screenshots, model choices, workflow events
  -> Knowledge Graph
  -> AI Pipeline
  -> Multi-Agent Workflow
  -> coding actions, documents, analysis, team handoffs

Core areas:

• FastAPI local workspace app
• Knowledge Graph storage and graph APIs
• AI pipeline and workflow designer
• Multi-agent handoff, review, retry, and replay records
• Local model management and model recommendation catalog
• VS Code / Cursor / VSCodium extension surface
• Personal and organization workspace boundaries

Documentation

• ARCHITECTURE.md — workspace, graph, pipeline, and model-management overview
• docs/architecture.md — full architecture reference
• PROJECT_PRINCIPLES.md — product principles
• AI_PHILOSOPHY.md — how AI is used in the workspace
• MODEL_POLICY.md — local model recommendation policy
• KNOWLEDGE_GRAPH.md — graph model and behavior
• docs/MULTI_AGENT_RUNTIME.md — multi-agent workflow runtime
• docs/WORKFLOW_DESIGNER.md — AI pipeline designer
• docs/REALTIME_COLLABORATION.md — realtime workspace events
• docs/ENTERPRISE.md — organization workspaces and SSO
• docs/PLUGIN_SDK.md — plugin SDK
• RELEASE_NOTES.md and docs/CHANGELOG.md

Release history

Version	Theme
3.1.0	Mainline platform completion — native /app workflows, Classic retired from normal paths, production embedding profiles, AgentRuntime/registries, hashed v3 assets
3.0.1	Release-blocker remediation — provider-backed embeddings (Hash/MLX/Ollama/OpenAI/Custom), unified AgentRuntime boundary, every v3 surface connected or clearly unavailable
3.0.0	v3 local-first AI workspace platform — /app, Native Chat, Knowledge Graph, Vector Index, Hybrid Search, workspace modes
2.2.7	Visual system stabilization — cohesive dark/light screens, crisp chat composer, dark graph canvas, Workspace OS polish
2.2.6	Token-native CSS foundation
2.2.5	Release hygiene hotfix — dark overlays, modal stack, cache-busting, favicon, and Telegram log masking
2.2.4	Chat dark-mode completion
2.2.3	Frontend stability and UX fixes
2.2.2	Frontend QA stabilization — mobile nav, admin actions, overflow fixes, and expanded visual tests
2.2.1	Frontend and UX overhaul for responsive workspace, themes, graph UX, admin reflow, and file attachment
2.2.0	Multimodal-first Knowledge Graph and local model source disclosure
2.1.0	Multi-agent workflow maturity
2.0.0	AI pipeline, workflow, and plugin platform foundation
1.7.0	Graph and collaboration
1.6.0	Product experience deepening

License

MIT