# Water Recirculation Alexa Skill

An Alexa skill that triggers water recirculation on Rinnai tankless water heaters.

## Usage

> "Alexa, ask house to start the hot water"

This will authenticate with the Rinnai API and start a 15-minute recirculation cycle.

## Building

Requires [Zig 0.15](https://ziglang.org/) and [mise](https://mise.jdx.dev/) for version management.

The build defaults to `aarch64-linux` for AWS Lambda Graviton (arm64) deployment.

```bash
# Debug build (arm64)
zig build

# Release build (arm64)
zig build -Doptimize=ReleaseFast

# Create Lambda deployment package
zig build -Doptimize=ReleaseFast package

# Build for native target (e.g., for local testing)
zig build -Dtarget=native
```

## Dependencies

- [lambda-zig](../../lambda-zig) - AWS Lambda runtime for Zig
- [controlr](../../controlr) - Rinnai API client (provides `rinnai` module)

## Deployment

### Prerequisites

- AWS CLI configured with appropriate credentials
- mise (for zig and bun version management)

### 1. Build the Package

```bash
mise exec -- zig build -Doptimize=ReleaseFast package
```

This creates `function.zip` containing the arm64 bootstrap executable.

### 2. Create Lambda Function (first time only)

```bash
aws lambda create-function \
  --function-name water-recirculation \
  --runtime provided.al2023 \
  --handler bootstrap \
  --architectures arm64 \
  --role arn:aws:iam::ACCOUNT_ID:role/lambda_basic_execution \
  --zip-file fileb://function.zip \
  --timeout 30 \
  --memory-size 128
```

### 3. Set Environment Variables

```bash
aws lambda update-function-configuration \
  --function-name water-recirculation \
  --environment "Variables={COGNITO_USERNAME=your@email.com,COGNITO_PASSWORD=your_password}"
```

### 4. Update Function Code (subsequent deploys)

```bash
mise exec -- zig build -Doptimize=ReleaseFast package

aws lambda update-function-code \
  --function-name water-recirculation \
  --zip-file fileb://function.zip
```

### 5. Deploy Alexa Skill

First time setup - configure ASK CLI (opens browser for Amazon login):

```bash
mise exec -- bunx ask-cli configure
```

Deploy the skill:

```bash
mise exec -- bunx ask-cli deploy
```

This will:
- Create the Alexa skill in your developer account
- Upload the interaction model
- Link to the Lambda endpoint

After deployment, add the Alexa Skills Kit trigger permission to Lambda:

```bash
aws lambda add-permission \
  --function-name water-recirculation \
  --statement-id alexa-skill \
  --action lambda:InvokeFunction \
  --principal alexa-appkit.amazon.com \
  --event-source-token amzn1.ask.skill.YOUR_SKILL_ID
```

## Project Structure

```
water_recirculation/
├── build.zig              # Build configuration (defaults to arm64-linux)
├── build.zig.zon          # Dependencies (lambda-zig, controlr)
├── ask-resources.json     # ASK CLI deployment config
├── src/
│   └── main.zig           # Alexa request handler
├── skill-package/
│   ├── skill.json         # Alexa skill manifest
│   └── interactionModels/
│       └── custom/
│           └── en-US.json # Interaction model
└── function.zip           # Lambda deployment package (after build)
```

## Sample Utterances

- "start the hot water"
- "turn on the hot water"
- "heat the water"
- "preheat the water"
- "start recirculation"
- "warm up the water"

## Lambda Details

- **Function**: `water-recirculation`
- **Region**: us-west-2
- **Architecture**: arm64 (Graviton)
- **Runtime**: provided.al2023
- **ARN**: `arn:aws:lambda:us-west-2:932028523435:function:water-recirculation`

## Alexa Skill

- **Skill ID**: `amzn1.ask.skill.c373c562-d574-4f38-bd06-001e96426d12`
- **Invocation**: "Alexa, ask house to..."

## License

MIT