# RSSCopilot Technical Architecture

## Overview

RSSCopilot is built on a modular architecture that integrates with Zotero's plugin system while maintaining high performance and reliability.

## System Components

### Core Components

```{mermaid}
graph TD
    A[Plugin Manager] --> B[Vector Service]
    A --> C[RSS Monitor]
    A --> D[UI Manager]
    B --> E[Database Service]
    C --> E
    D --> E
```

#### 1. Plugin Manager

- Handles plugin lifecycle
- Manages component initialization
- Coordinates services

#### 2. Vector Service

- Interfaces with language models
- Manages vector calculations
- Handles LSA space construction

#### 3. RSS Monitor

- Listens for Zotero RSS updates
- Processes new items
- Triggers relevance calculations

#### 4. UI Manager

- Renders relevance information
- Handles user interactions
- Manages settings interface

#### 5. Database Service

- Manages SQLite operations
- Handles data migrations
- Provides CRUD operations

### Data Flow

```{mermaid}
sequenceDiagram
    participant Z as Zotero
    participant P as Plugin Manager
    participant V as Vector Service
    participant D as Database
    participant U as UI

    Z->>P: RSS Update
    P->>V: Process New Items
    V->>D: Store Vectors
    V->>D: Calculate Relevance
    D->>U: Update Display
```

## Database Schema

### Entity Relationship Diagram

```{mermaid}
erDiagram
    papers ||--o{ paper_vectors : has
    papers {
        text id PK
        text title
        integer added_date
        integer last_updated
    }
    paper_vectors {
        text paper_id FK
        text model_id FK
        blob vector "dimension(384)"
        integer created_date
    }
    paper_vectors_index {
        blob vector "dimension(384)"
        integer _rowid "VSS0 index"
    }
    paper_vectors ||--|| paper_vectors_index : "vector index"
    rss_items ||--o{ rss_relevance : has
    rss_items {
        text id PK
        text title
        integer created_date
    }
    rss_relevance {
        text item_id FK
        text model_id FK
        blob vector "dimension(384)"
        blob history_vectors_space_svd_u "dimension(384)"
        blob recent_vectors_space_svd_u "dimension(384)"
        real history_relevance_score
        real recent_relevance_score
        integer updated_date
    }
    rss_relevance_index {
        blob vector "dimension(384)"
        blob history_vectors_space_svd_u "dimension(384)"
        blob recent_vectors_space_svd_u "dimension(384)"
        integer _rowid "VSS0 index"
    }
    rss_relevance ||--|| rss_relevance_index : "vector index"
    models ||--o{ paper_vectors : generates
    models ||--o{ rss_relevance : generates
    models {
        text id PK
        text name
        text api_config
        boolean is_active
        integer created_date
    }
```

## Implementation Details

### Vector Processing

```typescript
interface VectorService {
  generateVector(text: string): Promise<Float32Array>;
  calculateRelevance(vector1: Float32Array, vector2: Float32Array): number;
  updateLSASpace(vectors: Float32Array[]): void;
}
```

### Database Operations

```typescript
interface DatabaseService {
  addPaper(paper: Paper): Promise<void>;
  addVector(vector: PaperVector): Promise<void>;
  getRelevanceScores(itemId: string): Promise<RelevanceScore[]>;
  updateModel(model: Model): Promise<void>;
}
```

### UI Components

```typescript
interface UIManager {
  renderRelevanceColumn(): void;
  updateRelevanceScores(scores: Map<string, number>): void;
  showSettings(): void;
}
```

## Performance Considerations

### Optimization Strategies

1. **Vector Calculations**

   - Batch processing
   - Cached results
   - Incremental updates

2. **Database Operations**

   - Indexed queries
   - Bulk operations
   - Connection pooling

3. **Memory Management**
   - Vector compression
   - Resource cleanup
   - Lazy loading

### Monitoring and Metrics

- Response times
- Memory usage
- CPU utilization
- Error rates

## Security

### Data Protection

- Local processing
- Encrypted storage
- Secure API handling

### Error Handling

- Graceful degradation
- User notifications
- Error logging

## Testing Strategy

### Unit Tests

- Vector calculations
- Database operations
- UI components

### Integration Tests

- Plugin initialization
- RSS processing
- Model switching

### Performance Tests

- Load testing
- Stress testing
- Memory leaks

## Deployment

### Build Process

1. TypeScript compilation
2. Asset bundling
3. XPI packaging

### Release Process

1. Version bumping
2. Changelog generation
3. GitHub release
4. Update notification

## Future Considerations

### Scalability

- Support for larger libraries
- Multiple language models
- Distributed processing

### Extensibility

- Plugin API
- Custom models
- Additional metrics

## Contributing

See [CONTRIBUTING.md](./contributing.md) for development setup and guidelines.