The latest articles on DEV Community by GMM (@gmmb1). https://dev.to/gmmb1 https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3992214%2Fd4ad8cdc-deef-4fdd-bd5c-8832d121ebb9.jpg https://dev.to/gmmb1 en GMM Fri, 19 Jun 2026 09:19:32 +0000 https://dev.to/gmmb1/the-mental-state-monitor-and-ml-pipeline-1h6g https://dev.to/gmmb1/the-mental-state-monitor-and-ml-pipeline-1h6g <p>I've been building a local AI assistant called <strong>Arwanos</strong> that runs <br> 100% on your own machine — no cloud, no API keys, no data leaving <br> your device.</p> <p>The latest version (v10) adds something I'm genuinely proud of: <br> a <strong>Mental State Monitor</strong> — an ML pipeline that reads your personal <br> journal, cross-references your patterns against 7,557 real therapy <br> session examples, and generates psychological questions that get <br> <strong>deeper with every session</strong>.</p> <p>A few things it does that I think are interesting:</p> <ul> <li>Builds a psychological profile from your journal history before asking anything</li> <li>Questions never repeat — a 3-layer NLP check prevents it</li> <li>Runs entirely offline after a one-time dataset build</li> <li>Depth scales with session count (early sessions = surface, later = deep)</li> </ul> <p>I wrote a full technical breakdown of the ML pipeline on my site — <br> phases, dataset sources, anti-duplication logic, and how the insight <br> pipeline works after each session.</p> <p>👉 <strong><a href="https://gmmdev.online/my-thoughts/arwanos-v10-the-mental-state-monitor-and-ml-pipeline" rel="noopener noreferrer">Read the full article here</a></strong></p> <p>Source code: <a href="https://github.com/GMMB1/Transmitted-Ai" rel="noopener noreferrer"><img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fbt6rkmo5nbh9u5wgi7k7.png" alt=" " width="800" height="336"></a></p> <p><em>Questions or thoughts? Drop a comment — happy to discuss.</em></p> ai python machinelearning agents