Architecture Overview

NexusAI is a modular, memory-centric AI system designed for persistent, context-aware conversations. It separates concerns across different services that can be independently deployed and evolved

Core Design Principles

Decoupled layers: memory, inference, orchestration independent of eachother
Hybrid retrieval: semantic similarity (QDrant) combined with structured storage (SQLite) for flexible, ranked context assembly
Home lab: Services are properly distributed across the various nodes according to available hardware and resources

Memory Model

Memory is split between SQLite and QDrant, which both work together as a pair

SQlite: episodic interactions, entities, relationships, summaries
QDrant: vector embeddings for semantic similarity search

When recallng memory, QDrant returns IDs and similarity scores, which are used to fetch full content from SQLite. Neither SQlite or QDrant work in isolation

Hardware Layout

|---|---|---| | Main PC | local | Primary inference (RTX A4000 16GB) | | Mini PC 1 | 192.168.0.81 | Memory service, Embedding service, Qdrant | | Mini PC 2 | 192.168.0.205 | Orchestration service, Gitea |

Service Communication

All services expose a REST HTTP api. The orchestration service is the single entgry-point. Clients dont talk directly to the memory or inference services

Client └─► Orchestration (:4000) ├─► Memory Service (:3002) │ └─► Qdrant (:6333) │ └─► SQLite ├─► Embedding Service (:3003) └─► Inference Service (:3001) └─► Ollama

Technology Choices

Concern	Choice	Reason
Language	Node.js (JavaScript)	Familiar stack, async I/O suits service architecture
Package management	npm workspaces	Monorepo with shared code, no publishing needed
Vector store	Qdrant	Mature, Docker-native, excellent Node.js client
Relational store	SQLite (better-sqlite3)	Zero-ops, fast, sufficient for single-user
LLM runtime	Ollama	Easiest local LLM management, serves embeddings too
Version control	Gitea (self-hosted)	Code stays on local network

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