I built a 17-agent AI swarm on my phone — here's how

Описание и применение

Автор создал 17‑агентный AI‑сверм на Android‑телефоне, используя Termux и Python. Каждый агент выполняет простую задачу, а коммуникация реализована через файловую очередь. Это позволяет выполнять автоматический анализ данных и генерацию отчетов локально, но требует значительных усилий по настройке и ограничено ресурсами телефона.

Задача

Running a distributed, multi‑agent AI system entirely on a mobile device with limited resources.

Результат

The author successfully deployed a 17‑agent swarm on an Android phone, achieving decentralized intelligence for automated data analysis and report generation, albeit with limited efficiency and high technical complexity.

Рабочий процесс

• Install Termux from F‑Droid to get a Linux environment on the phone.
• Set up a lightweight Python environment and install dependencies (requests, sqlite3).
• Create SQLite database for data storage.
• Write individual agent scripts (e.g., data acquisition, preprocessing, analysis, report generation) each performing a single focused task.
• Implement a file‑based message queue: each agent publishes JSON messages to target agents’ input directories and subscribes by polling its own input directory.
• Use threading to run multiple agents concurrently within the same Python process or separate processes.
• Run agents in Termux, monitor logs, and iterate on error handling and performance.
• Validate that agents collaborate to produce aggregated reports and alerts.

Доказательства

I wanted a network of smaller, specialized agents. Each agent would be relatively simple, but collectively they could tackle tasks beyond the capacity of any single agent.

Источник

The biggest constraint was, of course, the limited resources of a phone. Forget heavy frameworks like TensorFlow or PyTorch. I needed something lightweight and efficient.

Источник

I ended up with a surprisingly effective solution: a file-based message queue.

Источник