# Architecture of the `rhailib_worker` Crate

The `rhailib_worker` crate implements a distributed task execution system for Rhai scripts, providing scalable, reliable script processing through Redis-based task queues. Workers are decoupled from contexts, allowing a single worker to process tasks for multiple contexts (circles).

## Core Architecture

```mermaid
graph TD
    A[Worker Process] --> B[Task Queue Processing]
    A --> C[Script Execution Engine]
    A --> D[Result Management]
    
    B --> B1[Redis Queue Monitoring]
    B --> B2[Task Deserialization]
    B --> B3[Priority Handling]
    
    C --> C1[Rhai Engine Integration]
    C --> C2[Context Management]
    C --> C3[Error Handling]
    
    D --> D1[Result Serialization]
    D --> D2[Reply Queue Management]
    D --> D3[Status Updates]
```

## Key Components

### Task Processing Pipeline
- **Queue Monitoring**: Continuous Redis queue polling for new tasks
- **Task Execution**: Secure Rhai script execution with proper context
- **Result Handling**: Comprehensive result and error management

### Engine Integration
- **Rhailib Engine**: Full integration with rhailib_engine for DSL access
- **Context Injection**: Proper authentication and database context setup
- **Security**: Isolated execution environment with access controls

### Scalability Features
- **Horizontal Scaling**: Multiple worker instances for load distribution
- **Queue-based Architecture**: Reliable task distribution via Redis
- **Fault Tolerance**: Robust error handling and recovery mechanisms

## Dependencies

- **Redis Integration**: Task queue management and communication
- **Rhai Engine**: Script execution with full DSL capabilities
- **Client Integration**: Shared data structures with rhai_dispatcher
- **Heromodels**: Database and business logic integration
- **Async Runtime**: Tokio for high-performance concurrent processing

## Deployment Patterns

Workers can be deployed as standalone processes, containerized services, or embedded components, providing flexibility for various deployment scenarios from development to production.