Entropia Riko

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Entropia Riko is a professional node-graph deep-learning editor — ComfyUI-style visual workflows for PyTorch (and optional TensorFlow/Keras), with a modular Blender-like workspace, live training curves, code export, a plugin system, and a built-in file manager.

It runs as a web app (browser) and ships an Electron shell so you can use it as a standalone desktop app — you choose.

Features

• 200+ nodes — math, tensor ops, neural layers/activations, attention, normalization, reductions, shape ops, einsum, losses, data loaders, model inference, subgraph references, Hugging Face (Diffusers / Transformers), and TensorFlow/Keras equivalents.
• Node graph canvas (React Flow) — right-click search menu, drag to connect, custom node cards with live output previews.
• Modular Blender-style workspace — split/merge/resize any panel (drag the corner grip; both resulting rounded windows are previewed in blue), switch any window's type, multiple workspace tabs with presets (Layout / Code / Training / MNIST Studio / Text→Image / …).
• Code editor — a Notepad-style window (File/Edit menus + toolbar: New, Open, Save, Undo/Redo, Cut/Copy/Paste) for previewing/editing exported PyTorch code.
• Train + live loss curve — stream per-step loss (SSE) into an SVG chart.
• Clean code export — PyTorch nn.Module and TensorFlow tf.keras.Model.
• Multi-file project export — File → Export Code → Export Project… writes a GitHub-layout PyTorch repo (README.md, requirements.txt, src/<name>.py) equivalent to the working folder.
• Subgraph navigation — double-click a graph_reference/import node to enter it; a Houdini-style breadcrumb (root / subgraph) in the top-left shows the level and exits back up.
• Multi-modal subgraph I/O — graph_input / graph_output accept a data_kind (tensor / text / json / image_tensor), not just numbers.
• Project-as-unit — work with a project folder (see templates/project/), not a single file; .riko/.ric files remain the on-disk format.
• Asset Library & New File — a working-directory file manager with drag-and-drop folders, right-click create/rename/delete, "expand full nodes" (inline a file's graph instead of a subgraph reference), and per-file PyTorch code preview.
• Built-in file explorer — Windows-style Import/Export (browse, back/forward, quick access, recent folders; copy files/folders instead of browser downloads).
• Plugin system — load plugins from .py files, toggle them on/off; managed in both a workspace panel and Preferences.
• Handwriting pad — draw a 28×28 digit and send it as a constant node to the MNIST example for inference.
• Themes — Light / Dark / System / Liquid Glass (Apple-style translucent).
• Detachable floating windows — all dialogs are draggable windows.
• Binary .ric format + ASCII .riko format with full metadata/settings.

Quick Start (browser)

cd entropia-riko
python -m venv .venv
. .venv/bin/activate            # Windows: .venv\Scripts\activate
pip install -r requirements.txt
npm install

# Terminal 1 — API (http://localhost:8000)
.venv/bin/python -m uvicorn src.server.app:app --reload --port 8000

# Terminal 2 — frontend (http://localhost:5173)
npm run dev

Open http://localhost:5173 (the /api routes proxy to :8000).

Quick Start (desktop app)

The Electron shell spawns the backend and opens a native window on the Vite dev server:

npm install --save-dev electron
npm run dev &                # keep the Vite dev server running
npm run desktop

Set RIKO_DEV_URL to point at another frontend URL if needed.

.riko / .ric file format

.riko is human-readable JSON; .ric is the same document zlib-compressed behind an ERIK magic header. Both carry version, metadata (name, app, appVersion), nodes, edges, and settings (theme, background image). See docs/FILE_FORMAT.md.

Plugins

Plugins live in plugins/*/ (a plugin.json manifest + an entry Python module that registers nodes via @register). Load more from a .py file and toggle them from the Plugins panel or Preferences → Plugins. Disabled plugins are skipped so their nodes stay unregistered. Bundled examples: example_plugin, math_extra, stat_extra.

Development commands

.venv/bin/python -m unittest discover -s tests -t .   # Python tests
npm test                                              # frontend tests (vitest)
npm run build                                         # type-check + production build
npm run dev                                           # Vite dev server
npm run desktop                                       # Electron desktop shell
.venv/bin/python scripts/make_brand_assets.py         # brand asset helper (see script)

Distribution / Release

Package a clean, shareable source ZIP (commits pending changes, then archives only tracked files — no node_modules, .venv, dist, caches, or backups):

.venv/bin/python scripts/release.py "release note"

Output: entropia-riko-release.zip in the parent directory (the working folder is never modified). It contains src/, public/, plugins/, examples/, templates/, electron/, scripts/, tests/, docs/, the READMEs, and config files — everything a recipient needs to pip install -r requirements.txt + npm install and run.

Project structure

src/
├── ui/         React app (canvas, panels, code editor, file manager, …)
├── core/       Tensor IR + graph document model (.riko/.ric)
├── runtime/    Registry, executor, PyTorch/TF codegen, trainer, subgraph
├── backend/    Torch device detection + conversion
├── nodes/      Node definitions
├── plugins/    Plugin loader
└── server/     FastAPI API server
plugins/        Bundled plugins
examples/       Ready-to-run pre-wired example graphs (dataset → model → loss → output)
electron/       Desktop shell (main + preload)
scripts/        Brand asset generator
public/brand/   logo.svg + hero.jpg (replace in place to rebrand)

Documentation

• User Guide — full manual (UI, nodes, training, export, API).
• docs/: APP_SPEC.md, APP_ARCHITECTURE.md, API.md, NODE_SYSTEM.md, DATA_FORMAT.md, FILE_FORMAT.md, UI_STANDARD.md, TORCH_BACKEND.md, CROSS_PLATFORM.md.

License

MIT