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

Project description

Lattice AI

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.

PyPI version npm version VS Code Marketplace Open VSX GitHub release License: MIT Python 3.11+ VS Code extension

Lattice AI demo

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:

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. Legacy /chat remains available as a rollback/debug path.
  • 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.
  • SSO for teams: organization workspaces can be paired with Okta or Microsoft Entra ID patterns for team access.

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.

v3.0.0 Highlights

Lattice AI v3.0.0 makes /app the primary workspace shell and ships the v3 backend retrieval stack together with the native frontend.

  • 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.
  • Legacy /chat remains reachable for rollback and debugging.
  • The default embedding signal is lattice-local-hash-v1, a deterministic local fallback. It is not described as a production semantic embedding model; future providers may include Ollama, MLX, OpenAI-compatible endpoints, and other local embedding runtimes.

Screenshots

Workspace

Workspace light theme

Workspace dark theme

Knowledge Graph

Knowledge Graph

AI Pipeline

AI Pipeline designer

Admin Dashboard

Admin dashboard

Mobile Responsive

Mobile responsive layout

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: the current default is lattice-local-hash-v1, a deterministic local fallback embedder for indexing and tests. It provides a stable vector signal without downloads or cloud calls; it is not a production semantic embedding model. Future provider support may include Ollama, MLX, OpenAI-compatible providers, and other local embedding runtimes.

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

Release history

Version Theme
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

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