AI in HomeStack
Artificial intelligence has become an integral part of my HomeStack infrastructure. Rather than relying on individual AI service subscriptions or managing multiple API keys across different applications, I've built a unified AI layer that serves all my projects.
This series covers how I've integrated AI capabilities into my service-oriented architecture, focusing on practical implementation rather than theoretical concepts.
Architecture Overview
My AI setup consists of two main components:
- AI-API: A self-hosted LiteLLM reverse proxy that unifies multiple AI providers behind a single endpoint
- Claudex: A secure, containerized development environment for AI agents
This architecture provides several key benefits:
- Single API endpoint for all AI providers (OpenAI, Anthropic, Google)
- Unified authentication using master keys instead of individual provider keys
- Cost tracking and rate limiting across all AI usage
- Secure development environment for AI agent experimentation
Posts
1. AI-API: Self-Hosted LiteLLM Reverse Proxy
How I unified multiple AI providers (OpenAI, Anthropic, Google) behind a single API endpoint using LiteLLM, with centralized authentication and cost tracking.
2. Claudex: Secure Containerized AI Development
A Docker-based environment for running AI agents like Claude Code and Codex with strict network isolation and Git-based workspace tracking.
3. AI Integration in HomeStack Services
Practical examples of how AI capabilities are embedded across my HomeStack services, from code generation to content creation.