Powered by Vision 50 Years PhoneSoftware should adapt to hardware, not force hardware replacement.
Setting For Me is a lightweight, local-first, open-source AI "Device Doctor" designed for existing and older Android smartphones. Instead of forcing users to navigate complex system menus, users simply state what they want in plain language. A tiny, local on-device model maps their intent to safe, verified actions.
Before (The Problem): Older phones suffer from software degradation, unwanted background bloat, and thermal throttling.After (Setting For Me): Your phone explains what is wrong in plain, honest language and fixes it with a single tap—no cloud uploads, no fake boosts, and no technical jargon required.
No Adware or Trackers: We will never bundle third-party cleaner tools, bloatware, or ad networks.No Fake RAM Boosts: We will never run fake memory clearing scripts that kill background apps only for Android to immediately restart them.No Data Uploads: Local-first architecture. All processing, logs, and execution happen strictly on-device.No Unverified Execution: The AI model cannot generate or execute arbitrary shell commands; it can only select pre-validated Action IDs from settings_map.json.
Phase 0 (Rule-Based Core): Search bar, 20-30 validated system actions, Device Health Report, Safety Gate, Evidence Ledger.Phase 1 (Model Frontend): Integrate on-device SmolLM2-360M-Instruct (Q4) for handling un-scripted query variations.Phase 2 (LoRA Fine-Tuning): Fine-tune the 360M model specifically on device-health intent mapping.Phase 3 (Cross-Service Diagnostics): Correlate thermal, battery, storage, and wake-lock telemetry to explain root causes.Phase 4 (Predictive Maintenance): Multi-week telemetry modeling to predict hardware/battery degradation before failure.
Distributed under the MIT License.