K9-AIF • Architecture Explorer

K9-AIF Graph Explorer

A curated architecture view of the K9-AIF framework, backed by a Neo4j knowledge graph. This explorer highlights the runtime flow, inference architecture, execution layer, supporting services, and framework contracts that shape K9-AIF as an architecture-first agentic AI framework.

● Interactive graph-backed experiences are in progress

Curated Architecture Views

Runtime Flow

Understand how requests move through K9-AIF at runtime — from routing and orchestration to agents, model selection, and inference execution.

BaseRouter → BaseOrchestrator → BaseAgent → ModelRouterFactory → K9ModelRouter → LLMFactory

Inference Architecture

Explore how K9-AIF separates model routing, inference abstraction, and model provisioning through factory and router patterns.

ModelRouterFactory → K9ModelRouter / DefaultModelRouter → BaseModelRouter → LLMFactory

Execution Layer

See how routers, orchestrators, squads, and agents work together to coordinate execution across the K9-AIF framework.

BaseRouter → BaseOrchestrator → FrameworkOrchestrator → BaseAgent

Supporting Services

View the persistence, queueing, retrieval, and monitoring components that support the broader execution lifecycle in K9-AIF.

BasePersistence / BaseQueue / BaseRetriever / BaseMonitor

Framework Contracts

Inspect the base contracts and implementation relationships that define how K9-AIF stays extensible, modular, and architecture-driven.

Base classes → implementation classes → semantic runtime relationships

Current Highlight: K9-AIF Runtime Backbone

BaseRouter ↓ ROUTES_TO BaseOrchestrator ↓ COORDINATES BaseAgent ↓ REQUESTS_MODEL_ROUTING ModelRouterFactory ↓ CREATES K9ModelRouter ↓ USES_FACTORY LLMFactory