GitHub - Stream44/FramespaceGenesis: TypeScript execution path based ontology-driven structural modeling tool with realtime interactive visualization.

Stream44 Studio
Open Development Project

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⚠️ Disclaimer: Under active development. Code has not been audited. APIs and interfaces are subject to change!

Framespace Genesis

Ontology-driven structural modeling tool for declaratively building multi-dimensional models with layered reactive functional data processing resulting in realtime interactive visualizations.

Usage

bun.sh is required.

After cloning run:

bun install

# Start the workbench
bun run dev

# Open browser
open http://localhost:3000

# Run tests (optional)
bun run test

Point your AI at docs/AI-MODEL-BUILDING.md and make some changes to the examples.

Quadrant & Codepath View Examples

See docs/Roadmap.md for planned visualization libraries.

Problem Statement

Semantic models are an indispensable tool for model-driven development and structuring context for AI.

Semantic modeling becomes a complex task when combining multiple models horizontally and vertically leading to slow progress in practical applications of comprehensive models.

Knowledge models require better tooling and toolchain integration to evolve into a well-understood and leveraged technology.

Much focus is on storing the data of a system in a graph.

We are focused on storing the structure of a system in a graph to provide the data-processing indepent blueprint for a distributed system.

Innovation

Framespace Genesis uses a novel approach to create complex layered models by taking a code-first approach that feels familiar and is efficient to work with by hand and AI.

Models are constructed as code components with declarative mappings to other components and executed by creating and resolving a promise chain across component method invocations. This is made possible by the encapsulate library.

A code-first approach to building semantic entities allows for hoisting functional processing nodes into a graph and for the construction of dynamic graphs with very litte tooling. When the tools disappear and the abstraction is clear new possibilities arise.

Purpose

Explore model development using the encapsulate approach and layered functional processing in a structured graph to discover sclable graph processing patterns.
Explore the creation of interactive visual interfaces driven exclusively by models.

Modeling Layers

Visual models running in the workbench are constructed by calling model APIs implemented in various lower layers.

L3: Model Server

Exposes model APIs for querying data. In the process model layers are linked into reactive data processing graphs.

L4: Space Models

Space models are modular & self-contained graph models with strict boundaries.

They are infinite data substrates constructed from simple repeating primitives.

Capsular
A model that encodes component-based implementation architectures into capsule spines.
The schema is dictated by https://github.com/Stream44/encapsulate
Implementation details: L4-space-models/Capsular/README.md

L6: Semantic Models

Semantic models define dimensions in a space by structuring primitives into linked objects with specific properties.

Capsular / Capsule Spine
Conveniently query Spine Instance Trees, Capsule Source Trees and Membrane Events in Capsular spaces.

L8: View Models

View models structure one or more semantic models into derived layout visual canvases.

See L8-view-models/README.md for details.

L13: Workbench

The framespace workbench UI SPA implementation that connects to the Model Server.

Provenance

Repository DID: did:repo:e7b46f0978c2cc02461b480b99a6589a2b6fa888

Inception Mark

Current Mark

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