Solo Dev Spent Six Months on an On-Device Android Agent Built as an Editable Graph, Not a Prompt
alexeyw · reddit · 2026-09-06
A developer built an Android on-device agent over six months of nights and weekends; it's now on Google Play and open-sourced under Apache 2.0. The core bet: an editable graph of typed nodes instead of one big prompt — a 2–4B model on a phone falls apart on multi-hop tasks, so the graph holds the task while each node gets model-sized work. Structured-output nodes run through a validation gate with error-quoting retries (two by default, configurable 0–4).
- Stack: runs on-device via LiteRT-LM with Gemma 4 E2B/E4B, or any .litertlm URL
- Nodes: 14 node types (input, on-device LLM, cloud LLM, tool call, condition, intent router, decomposition, queue, evaluation, summary, clarification, nested pipeline, skill, output); editable by dragging in-app or via a desktop HTML editor with JSON import
- Tools & safety: local actions via AppFunctions, external via MCP; destructive or sensitive actions require explicit confirmation (including tap-to-confirm notifications for background triggers); skill tool allowlists are enforced in the executor, not requested in prompts
- External driving: Tasker/MacroDroid or an adb one-liner can invoke one bound pipeline; off by default, non-bound requests are refused and journaled
- Optional cloud: OpenAI, Anthropic, Gemini, DeepSeek and Ollama as node types; nothing leaves the phone unless a node says so
- Autonomy ceilings: limit-stopped runs report as such; circular runs are detected and stopped
- Measured (author, Galaxy S25 Ultra): clean install to first useful output 5 min 22 s
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