> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agentium.in/llms.txt
> Use this file to discover all available pages before exploring further.

# Edge & IoT

> Deploy AI agents on Raspberry Pi and edge devices with IoT toolkits, local LLM inference, and cloud sync.

# Agentium Edge

Run AI agents on constrained hardware like Raspberry Pi — with IoT toolkits, local LLM inference via Ollama, and optional cloud synchronization.

No other Node.js/TypeScript agent framework has native edge/IoT support. Agentium can run on a Pi 4 with 2 GB RAM using a 1B-parameter model.

***

## Why Edge?

* **Local inference** — keep data on-device with Ollama and small models
* **Hardware control** — GPIO pins, I2C sensors, camera, BLE from your agent
* **Offline-first** — queue events locally, sync when cloud is available
* **Resource-aware** — automatic throttling when CPU is hot or memory is low

***

## Quick Start

```bash theme={null}
npm install @agentium/edge
```

```typescript theme={null}
import { Agent, ollama } from "@agentium/core";
import {
  SystemToolkit,
  GpioToolkit,
  EdgeRuntime,
  edgePreset,
  ensureOllama,
  registerEdgeToolkits,
} from "@agentium/edge";

// Register edge toolkits in the catalog (for Admin UI)
registerEdgeToolkits();

// Ensure Ollama is running
await ensureOllama();

const preset = edgePreset("pi5-8gb");

const system = new SystemToolkit();
const gpio = new GpioToolkit({ chipNumber: 4, allowedPins: [17, 27, 22] });

const agent = new Agent({
  name: "pi-agent",
  model: ollama(preset.recommendedModel),
  instructions: "You control a Raspberry Pi. Monitor system health and control GPIO pins.",
  tools: [...system.getTools(), ...gpio.getTools()],
});

const runtime = new EdgeRuntime({ preset, agent });
await runtime.start();

const result = await agent.run("What is the CPU temperature and memory usage?");
console.log(result.finalOutput);
```

***

## Supported Devices

| Device      | RAM  | Recommended Model | Preset ID |
| ----------- | ---- | ----------------- | --------- |
| Pi 4 (2 GB) | 2 GB | TinyLlama 1.1B    | `pi4-2gb` |
| Pi 4 (4 GB) | 4 GB | TinyLlama 1.1B    | `pi4-4gb` |
| Pi 4 (8 GB) | 8 GB | Llama 3.2 1B      | `pi4-8gb` |
| Pi 5 (4 GB) | 4 GB | Llama 3.2 1B      | `pi5-4gb` |
| Pi 5 (8 GB) | 8 GB | Phi-3 Mini 3.8B   | `pi5-8gb` |

***

## Package Structure

```
@agentium/edge
├── Toolkits
│   ├── SystemToolkit     — CPU, memory, disk, network (zero deps)
│   ├── GpioToolkit       — GPIO read/write/watch/PWM
│   ├── CameraToolkit     — libcamera capture/record/stream
│   ├── SensorToolkit     — I2C sensors (BME280, BMP180)
│   ├── BleToolkit        — Bluetooth Low Energy
│   └── ServoToolkit      — Hobby servo control
├── Runtime
│   ├── EdgeRuntime       — Watchdog, resource monitor, health endpoint
│   ├── edgePreset()      — Device-specific configuration
│   └── Ollama helpers    — ensureOllama, pullModel, recommendModel
└── Sync
    └── EdgeCloudSync     — Heartbeat, config pull, offline queue
```

***

## Hardware Dependencies

All hardware libraries are **optional peer dependencies**. Install only what you need:

```bash theme={null}
# GPIO (Pi 5 compatible)
npm install node-libgpiod

# I2C sensors
npm install i2c-bus

# Bluetooth BLE
npm install @stoprocent/noble
```

The `SystemToolkit` and `CameraToolkit` have **zero native dependencies** — they read from `/proc/`, `/sys/`, and shell out to `libcamera-still`.