// the find
ITSpecialist111/ai_automation_suggester
This custom Home Assistant integration automatically scans your entities, detects new devices, and uses AI (via cloud and local APIs) to suggest tailored automations. It supports multiple AI providers, including OpenAI, Anthropic, Google, Groq, Ollama and more! The integration provides automation suggestions via HASS notifications
A Home Assistant custom integration that sends your entity/device state to an AI provider and gets back suggested automation YAML. Supports 10+ providers including local ones (Ollama, LocalAI). Good fit for HA users who want automation ideas but don't want to write YAML from scratch.
- Provider breadth is genuinely useful: supporting Ollama/LocalAI means privacy-conscious users can keep all data local, and the model catalog with per-provider defaults and custom model name override is pragmatic.
- Avoids the openai Python SDK entirely and uses plain HTTP calls, which is the right call for a HA custom component where SDK version conflicts are a real operational headache.
- Suggestion history with accept/decline/dismiss review states and a REST API for the bundled Lovelace card shows thought about the actual UX workflow, not just dumping text into a notification.
- Tests exist for the non-trivial utility modules (endpoint_utils, language_utils, model_catalog, suggestions parsing) and CI runs hassfest and HACS validation, which is above average for a custom component.
- The model catalog lists model IDs like 'gpt-5.4-mini', 'claude-sonnet-4-6', and 'gpt-5.5-pro' that don't exist as of mid-2025 — this looks like aspirational/hallucinated model names baked into code, which will silently produce API errors for users who trust the defaults.
- The core value proposition — quality of YAML suggestions — depends entirely on prompt engineering that isn't versioned or user-visible, and there's no mechanism to detect when returned YAML references non-existent entity IDs or service calls, beyond a simple parse check.
- Test coverage only hits utility functions; coordinator.py and api.py (the actual API call logic and HA integration wiring) have no tests, so regressions in the critical path will only surface in production.
- Sending potentially hundreds of entity states and attributes to cloud APIs on a weekly schedule with no built-in cost estimation or token usage reporting is a footgun for users with large installations; the entity_limit is manual and easy to misconfigure.