Homelab AI Sentinel: Self-Hosted Monitoring Assistant with LLM Integration

What It Does
Homelab AI Sentinel takes monitoring webhooks and runs them through an LLM to generate a plain-English diagnosis that includes what happened, what likely caused it, and what to check first.
Key Features
- AI Integration: The AI integration is contained in a single file. Swap the provider by changing one file while leaving the rest of the stack untouched.
- Default LLM: Ships with Gemini 2.5 Flash by default.
- Local Inference Support: Ollama and LM Studio work out of the box for fully local inference with nothing leaving your network.
- Alert Sources: Supports 11 alert sources including Uptime Kuma, Grafana, Prometheus, Zabbix, and Docker Events.
- Notification Platforms: Supports 10 notification platforms including Discord, Slack, Telegram, WhatsApp, Signal, and Ntfy.
- API Compatibility: Works with any OpenAI-compatible endpoint — if it speaks the API, it works.
Setup
Deployment is via docker compose up. The tool is available on GitHub.
📖 Read the full source: r/LocalLLaMA
👀 See Also

Phalanx CLI coordinates multiple AI agents for automated code-review cycles
A developer built Phalanx, a CLI tool that coordinates AI agents from different providers: Codex handles coding, Claude Opus performs code review, and Claude Sonnet orchestrates the loop. A companion tool called Codebones compresses repositories to structural maps to reduce token usage.

BusyDog Desktop: A Local AI Agent with P2P Networking for Mac
BusyDog Desktop is a local AI agent that runs Claude directly on a Mac, can read/write files, run terminal commands, control browsers, and connect with other agents via a P2P network using Hyperswarm DHT and a custom BDP protocol.

Using pre-commit to improve AI-generated code quality and security
A developer shares their pre-commit configuration for Go and Java projects, using tools like golangci-lint, govulncheck, and checkov to catch vulnerabilities and quality issues in AI-generated code before commit.

Tri-Node Memory: Open Source Persistent Agent Memory with Human/Agent Vault Separation
Tri-Node Memory is a lightweight architecture that separates an AI coding agent's memory from the human's persistent journal using two Obsidian vaults. The agent reads from the human vault but writes only to its own, never crossing boundaries without explicit permission.