Local AI Platform (Reference Implementation)

ai, local-ai, infrastructure, homelab, llama-cpp, self-hosted, agents

Overview

Local AI Platform is a self-hosted AI infrastructure project designed to explore what practical agent-based workflows look like when run entirely on local hardware.

The system separates the inference backend from client tools using an OpenAI-compatible API, allowing multiple applications to interact with the same model environment without being tied to a specific runtime.

This architecture enables tools such as interactive chat interfaces, coding agents, and assistant-style workflows to operate against a shared local inference backend.

Key Capabilities

  • Self-hosted inference — models run entirely on local hardware without relying on external APIs
  • API boundary architecture — clients interact through an OpenAI-compatible interface
  • Multi-tool interoperability — multiple AI tools share a single inference backend
  • Agent workflow support — coding agents and assistant agents operate against the same system
  • Reproducible architecture — the full configuration is documented as a reference implementation

Use Cases

This project is intended as a practical testbed for exploring local AI infrastructure and agent workflows.

It is well suited for:

  • Homelabs experimenting with self-hosted AI systems
  • Infrastructure engineers evaluating local inference stacks
  • Developers testing agent tools against a local backend
  • Environments where reducing reliance on hosted AI services is desirable

Architecture Summary

The platform uses a layered architecture centered around an OpenAI-compatible API boundary.

Clients:

  • OpenWebUI — interactive interface for prompts and experimentation
  • OpenCode — coding agent used for targeted development tasks
  • OpenClaw — assistant-style agent integrated with messaging platforms

Backend:

  • llama.cpp inference server exposing an OpenAI-compatible API

Hardware:

  • Dual RTX 4070 GPUs (24GB VRAM total) for GPU-accelerated inference
  • CPU with integrated graphics for host display and orchestration

This separation allows multiple tools to operate against the same backend while keeping the inference runtime interchangeable.

Source Code

The full implementation, configuration, and documentation are available on GitHub:

https://github.com/alexbakertech/local-ai-platform

The repository includes architectural documentation, backend service configuration, agent tool integrations, and notes on design decisions and observed system limitations.