I wanted to ask an AI questions about my Garmin health data — sleep, HRV, stress, recovery — without sending it to OpenAI or any other cloud service.
Built this with Claude as my coding partner. I can't write Python. It works anyway.
What it does: downloads your complete Garmin Connect data locally, exports to Excel and interactive HTML dashboards, generates RAG-optimised JSON summaries for Ollama/AnythingLLM, and includes a Windows desktop app so no terminal is needed.
Everything runs on your own machine. Nothing leaves it.
GitHub: github.com/Wewoc/garmin_collector
Quick question, which models are you using with Ollama for analysis? I’ve been testing a few locally, and hardware requirements vary a lot, so not everyone can run the heavier ones.
Have you done any benchmarking or have a recommended model for this use case?
AnythingLLM + qwen2.5:14b is what I use — good for pattern recognition across metrics you wouldn't think to look for manually.
For everything else the HTML dashboards honestly do a better job. garmin_analysis.html shows your daily values, personal 90-day baseline and age/fitness reference ranges all in one view. Most questions answer themselves just by looking at it.