LangTailor Canvas

Visual LangGraph IDE — design agent workflows on a drag-and-drop canvas, then export clean, runnable Python.

LangTailor Canvas turns any *.langstitch.json file into a live visual editor for LangGraph applications. Drag in LLM nodes, tools, agents, RAG pipelines, guardrails, and routers; wire them together; and export a buildable, multi-module Python project — no lock-in, no rewrite.

It ships built into the LangTailor desktop IDE and installs into any VS Code–compatible editor (VS Code, VSCodium, Cursor, Gitpod, Theia) from Open VSX.

Features

Visual graph editor — design LangGraph StateGraphs on an infinite canvas with drag-and-drop nodes, typed ports, and auto-layout.
Rich node palette — LLM, Tool, Agent, RAG Agent, Multi-Intent Classifier, Decision, Function, and Subgraph nodes, plus your own custom components.
Asset designers — author Skills, Guardrails, Business Rules, Personas, and RAG pipelines through dedicated forms; each exports to its own Python module.
Custom Component Designer — build reusable nodes, connectors, and adaptors with a typed config schema and a safe codegen template (no eval, secrets emitted as os.environ.get(...)).
Python 3.13 export — generate a clean multi-module project that runs on the langstitch-sdk — the same scaffold the SDK CLI produces, so canvas and code stay in sync.
Native editor integration — built as a VS Code custom editor, so undo/redo, dirty-state, and save all work exactly as you expect.
Marketplace, in-editor — browse and add community plugins and connectors without leaving the canvas, or publish your own at marketplace.langstitch.com.
Sign in with GitHub — authenticate to LangStitch right from the editor (secure browser-based OAuth) to sync your plugins to the LangTailor desktop IDE.
Local toolchain — Build, Run, Test, Debug, Version, and Deploy run on your machine with keyboard shortcuts (Ctrl/Cmd+Alt+B/R/T/D/V and Ctrl/Cmd+Alt+Shift+D for deploy). No server required.

Getting started

Install the extension from Open VSX, or use the LangTailor desktop IDE where it's built in.
```
# VSCodium / CLI
codium --install-extension langstitch.langtailor-canvas
```
Create a graph — run LangTailor: New Graph from the Command Palette, or open any existing *.langstitch.json file.
Design your agent workflow on the canvas — add nodes, configure them in the property panel, and wire the edges.
Export to Python from the Platform panel and run it:
```
pip install "langstitch-sdk[all]"
python -m app
```

The LangStitch SDK

Exported projects run on the open-source LangStitch SDK — Python decorators, typed config, and a CLI for building LangGraph apps:

pip install langstitch-sdk
langstitch new my-agent

Docs: langstitch.com/docs · PyPI: langstitch-sdk

Building from source

The canvas source is vendored in _canvas/ — no separate checkout needed.

npm install        # install build deps
npm run build      # build the webview bundle (_canvas/src) + extension host
# then press F5 in VS Code to launch the "LangTailor Canvas Extension" host

Open or create a *.langstitch.json file to launch the canvas editor.

Workflow	Trigger	Purpose
`ci.yml`	push / PR to `main`	Build the VSIX (smoke test)
`release.yml`	tag `langtailor-v*` or manual	VSIX + Windows/macOS portable bundles → GitHub Release
`openvsx.yml`	release published or manual	Publish the extension to Open VSX

To cut a release: bump version in package.json, then tag langtailor-v<version> and push (or run the LangTailor Release workflow). See docs/OPENVSX_SETUP.md for Open VSX publishing.

LangTailor Canvas

LangStitch

LangTailor Canvas

Features

Getting started

The LangStitch SDK

Links

Building from source

License