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

        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

        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

        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

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

Database Operations

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

UI Components

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 for development setup and guidelines.