Component Specification: MALENIO Gmail AI Assistant

This document provides detailed specifications for each component of the MALENIO Gmail AI Assistant. It defines the responsibilities, interfaces, dependencies, and implementation considerations for every component identified in the Technical Architecture document. These specifications serve as the blueprint for development teams, ensuring that each component meets its requirements and integrates correctly with other parts of the system.

Executive Summary

This document provides detailed specifications for each component of the MALENIO Gmail AI Assistant. It defines the responsibilities, interfaces, dependencies, and implementation considerations for every component identified in the Technical Architecture document. These specifications serve as the blueprint for development teams, ensuring that each component meets its requirements and integrates correctly with other parts of the system.

The specifications are designed to support MALENIO’s core architectural decisions, particularly the commitment to local AI processing, privacy-first design, and seamless Gmail integration through Chrome extension technologies.

For web-based components, MALENIO leverages NextJS for the frontend and FastAPI for the backend, creating a robust, type-safe, and high-performance technology stack. This combination provides excellent developer experience, automatic API documentation, strong typings across frontend and backend, and modern features like server-side rendering and asynchronous API endpoints.

Component Design Principles

All MALENIO components adhere to the following design principles:

  1. Privacy by Design: Components never transmit email content outside the user’s device
  2. Graceful Degradation: Components handle failure states elegantly
  3. Performance Efficiency: Components optimize for minimal resource consumption
  4. Modular Architecture: Components have clear boundaries and interfaces
  5. Adaptive Experience: Components adjust to user hardware capabilities
  6. Seamless Integration: Components blend naturally with the Gmail experience
  7. Progressive Disclosure: Components reveal complexity progressively as needed

1. Chrome Extension Framework Components

1.1 Background Service Worker

Purpose

The central orchestrator for the extension, managing lifecycle events and coordinating communication between components.

Interface

  • External Interfaces:
    • Chrome Extensions API
    • Ollama API via localhost connection
    • Gmail API (authenticated)
  • Internal Interfaces:
    • Message-passing interface to content scripts
    • State management for popup interface
    • Event system for component coordination

Dependencies

  • Chrome Extension Framework
  • Local Storage Manager
  • Ollama Integration Module

Implementation Requirements

  • Programming Language: JavaScript/TypeScript
  • Key Libraries: Chrome Extension APIs, WebSocket
  • State Management: Must maintain state across browser sessions
  • Error Handling:
    • Must recover from Ollama connection failures
    • Must handle Gmail API authentication issues
    • Must log errors with appropriate verbosity

Performance Requirements

  • Low CPU footprint (<5% average usage)
  • Memory usage <50MB at idle
  • Startup time <500ms

Security Considerations

  • Never stores Gmail credentials, only OAuth tokens
  • Uses secure local storage for sensitive data
  • Implements proper permission handling

Testing Strategy

  • Unit tests for all service worker functions
  • Integration tests for Chrome API interactions
  • Mock testing for Ollama communication
  • Stress testing for resource utilization

1.2 Content Scripts

Purpose

Scripts injected into the Gmail web application to interact with and modify the Gmail interface.

Interface

  • External Interfaces:
    • Gmail DOM (read/write)
    • Gmail web application events
  • Internal Interfaces:
    • Message passing to background service worker
    • Custom event listeners for UI components

Dependencies

  • Gmail Interface Layer
  • Background Service Worker
  • UI Components

Implementation Requirements

  • Programming Language: JavaScript/TypeScript
  • Key Libraries: DOM manipulation, MutationObserver
  • DOM Interaction:
    • Must use data attributes for DOM selection, not CSS classes
    • Must implement changes through shadow DOM where possible
    • Must handle Gmail DOM structure changes gracefully

Performance Requirements

  • Initialization in <200ms
  • UI updates in <50ms
  • No visible rendering delays

Security Considerations

  • Content scripts operate in isolated worlds
  • No direct access to Gmail JavaScript context
  • Careful handling of email content in DOM

Testing Strategy

  • UI automated testing with various Gmail configurations
  • Compatibility testing across Gmail versions
  • Race condition testing for DOM mutations
  • Visual regression testing for UI modifications

1.3 Popup Interface

Purpose

User-facing control panel for configuration, status monitoring, and manual actions.

Interface

  • External Interfaces:
    • User interaction events
    • Chrome storage for settings
  • Internal Interfaces:
    • Message passing to background service worker
    • Access to extension state

Dependencies

  • Background Service Worker
  • Extension Storage
  • Model Manager

Implementation Requirements

  • Programming Language: TypeScript, HTML, CSS
  • Framework: React or Vue.js
  • UI Components:
    • Settings toggle controls
    • Model selection dropdown
    • Status indicators
    • Privacy control panel
    • Help and documentation links

Performance Requirements

  • Load time <300ms
  • Responsive UI with <50ms input latency
  • Smooth animations (60fps)

Security Considerations

  • No exposure of sensitive data in UI
  • Input validation for all configuration settings
  • Clear privacy indicators

Testing Strategy

  • User experience testing for intuitive controls
  • Cross-browser compatibility testing
  • Accessibility compliance testing
  • Usability testing with various device sizes

1.4 Extension Storage

Purpose

Secure persistence layer for extension state and user preferences.

Interface

  • External Interfaces:
    • Chrome Storage API
  • Internal Interfaces:
    • Data access methods for other components
    • Change listeners for state updates

Dependencies

  • Chrome Extension Framework
  • Privacy Control System

Implementation Requirements

  • Programming Language: TypeScript
  • Storage Mechanisms:
    • chrome.storage.sync for cross-device preferences
    • chrome.storage.local for device-specific data
    • IndexedDB for larger datasets

Performance Requirements

  • Read operations <50ms
  • Write operations <100ms
  • Storage size <5MB for synced data

Security Considerations

  • Encryption for sensitive local data
  • Clear data boundaries for what can be synced
  • Avoidance of personally identifiable information in sync storage

Testing Strategy

  • Unit tests for storage operations
  • Data persistence testing across sessions
  • Sync behavior testing across devices
  • Quota limit testing

2. Gmail Interface Layer Components

2.1 Gmail API Client

Purpose

Handles authenticated programmatic access to Gmail data and operations.

Interface

  • External Interfaces:
    • Gmail REST API
    • OAuth authentication flow
  • Internal Interfaces:
    • Promise-based API for email operations
    • Pagination handling for large result sets
    • Event emitters for operation status

Dependencies

  • Background Service Worker
  • Local Storage Manager
  • Privacy Control System

Implementation Requirements

  • Programming Language: TypeScript
  • Key Libraries: Gmail API SDK, OAuth2 client
  • API Usage:
    • Must implement request batching
    • Must handle rate limiting gracefully
    • Must cache frequently accessed data

Performance Requirements

  • API request completion <500ms average
  • Support for handling up to 1000 messages in batch operations
  • Efficient pagination for large mailboxes (>100,000 emails)

Security Considerations

  • Minimal scope OAuth permissions
  • Token refresh handling without user disruption
  • Secure token storage

Testing Strategy

  • Mock testing for API interactions
  • Rate limit behavior testing
  • Authentication flow testing
  • Error recovery testing

2.2 DOM Integration Module

Purpose

Directly interacts with and modifies the Gmail web interface.

Interface

  • External Interfaces:
    • Gmail DOM structure
    • Gmail event system
  • Internal Interfaces:
    • Component rendering system for UI injections
    • DOM event listeners for user interactions

Dependencies

  • Content Scripts
  • UI Components

Implementation Requirements

  • Programming Language: TypeScript
  • Key Techniques:
    • MutationObserver for Gmail DOM changes
    • Shadow DOM for UI injections
    • Event delegation for performance
    • Throttled updates to prevent UI flickering

Performance Requirements

  • DOM updates <100ms
  • Observer initialization <150ms
  • Low impact on Gmail rendering performance

Security Considerations

  • No direct script injection to avoid XSS
  • Careful handling of email content from DOM
  • No storage of DOM content outside extension context

Testing Strategy

  • Compatibility testing across Gmail versions
  • UI integration testing
  • Performance impact testing
  • Visual regression testing

2.3 Email Parser

Purpose

Extracts structured data from raw email content.

Interface

  • External Interfaces:
    • None (internal component)
  • Internal Interfaces:
    • Parsing methods for email content
    • Structured data output format

Dependencies

  • Gmail API Client
  • DOM Integration Module
  • Inference Processor

Implementation Requirements

  • Programming Language: TypeScript
  • Key Libraries: Email parsing, MIME handling, HTML sanitization
  • Parsing Capabilities:
    • HTML and plaintext email formats
    • Attachments identification
    • Conversation threading
    • Quoted content detection
    • Signature extraction
    • Entity recognition

Performance Requirements

  • Parse speed >10 emails/second
  • Memory efficient handling of large emails

Security Considerations

  • HTML sanitization to prevent XSS
  • Content isolation during parsing
  • No content persistence beyond necessary scope

Testing Strategy

  • Unit testing with diverse email formats
  • Performance testing with large emails
  • Boundary case testing
  • Internationalization testing

2.4 Advanced Gmail API Integration

Purpose

Leverages Gmail API capabilities for powerful search and batch operations.

Interface

  • External Interfaces:
    • Gmail API (batch operations endpoints)
  • Internal Interfaces:
    • Search query builder
    • Batch operation manager
    • Label orchestration system

Dependencies

  • Gmail API Client
  • Local AI Processing Engine
  • Advanced Search and Batch Action Interface

Implementation Requirements

  • Programming Language: TypeScript
  • Key APIs:
    • users.messages.batchModify
    • users.messages.list with query parameters
    • users.labels management

Performance Requirements

  • Support for batch operations on up to 1000 messages
  • Search response time <1s for most queries
  • Efficient pagination handling for large result sets

Security Considerations

  • Transactional integrity for batch operations
  • Proper error handling for failed operations
  • Protection against accidental mass modifications

Testing Strategy

  • Unit testing for query building
  • Integration testing with Gmail API
  • Performance testing on large mailboxes
  • Rollback testing for failed operations

3. Local AI Processing Engine Components

3.1 Ollama Integration

Purpose

Establishes and manages connection to the local Ollama instance for AI model execution.

Interface

  • External Interfaces:
    • Ollama API (localhost:11434)
    • WebSocket connection for streaming
  • Internal Interfaces:
    • Model execution methods
    • Connection status events
    • Configuration methods

Dependencies

  • Background Service Worker
  • Model Manager
  • Local Storage Manager

Implementation Requirements

  • Programming Language: TypeScript
  • Connection Management:
    • Automatic connection establishment
    • Heartbeat monitoring
    • Reconnection strategies
    • Graceful fallback when Ollama unavailable

Performance Requirements

  • Connection establishment <500ms
  • Request timeout handling (>10s)
  • Support for streaming responses

Security Considerations

  • Localhost-only connections
  • No external network transmission of email content
  • Validation of Ollama responses

Testing Strategy

  • Connection testing under various conditions
  • Error handling testing
  • Performance testing with different models
  • Recovery testing from connection failures

3.2 Model Manager

Purpose

Handles AI model operations, selection, and configuration.

Interface

  • External Interfaces:
    • Ollama model repository API
  • Internal Interfaces:
    • Model information and status
    • Model selection and switching
    • Configuration methods

Dependencies

  • Ollama Integration
  • Background Service Worker
  • Model Management Interface

Implementation Requirements

  • Programming Language: TypeScript
  • Model Management:
    • Dynamic discovery of available models
    • Hardware capability detection
    • Model download and update handling
    • Version tracking

Performance Requirements

  • Model switching <2s
  • Background downloading without UI disruption
  • Efficient model caching

Security Considerations

  • Verification of model integrity
  • Safe model storage
  • Resource limitation enforcement

Testing Strategy

  • Model compatibility testing
  • Download reliability testing
  • Model switching testing
  • Hardware detection accuracy testing

3.3 Inference Processor

Purpose

Processes AI inferences for email analysis and response generation.

Interface

  • External Interfaces:
    • None (internal component)
  • Internal Interfaces:
    • Inference methods for different tasks
    • Result processing and formatting

Dependencies

  • Ollama Integration
  • Email Parser
  • Learning Module

Implementation Requirements

  • Programming Language: TypeScript
  • Inference Types:
    • Classification and tagging
    • Semantic understanding
    • Sentiment analysis
    • Entity recognition
    • Response generation
    • Instruction parsing

Performance Requirements

  • Inference time <2s for typical tasks
  • Efficient handling of concurrent requests
  • Adaptive resource usage based on hardware

Security Considerations

  • Input sanitization for prompt injection prevention
  • Output validation
  • No persistent storage of email content

Testing Strategy

  • Accuracy testing against human benchmarks
  • Performance testing with varying input sizes
  • Consistency testing across models
  • Adversarial input testing

3.4 Learning Module

Purpose

Adapts to user behavior and improves system performance over time.

Interface

  • External Interfaces:
    • None (internal component)
  • Internal Interfaces:
    • Learning methods
    • Personalization data access
    • Feedback processing

Dependencies

  • Local Storage Manager
  • Inference Processor
  • Privacy Control System

Implementation Requirements

  • Programming Language: TypeScript
  • Learning Capabilities:
    • User preference tracking
    • Communication style modeling
    • Feedback incorporation
    • Adaptive suggestion refinement

Performance Requirements

  • Incremental learning with minimal overhead
  • Efficient storage of learning data <10MB
  • Learning improvements visible within 5-10 interactions

Security Considerations

  • Anonymized learning data
  • Local-only storage of personal patterns
  • User control over learning features

Testing Strategy

  • Improvement measurement testing
  • Storage efficiency testing
  • User simulation for learning patterns
  • Cross-user isolation testing

4. Data Management System Components

4.1 Local Storage Manager

Purpose

Ensures secure persistence of application data.

Interface

  • External Interfaces:
    • Browser storage APIs
    • IndexedDB
  • Internal Interfaces:
    • Data access methods
    • Storage policy enforcement
    • Encryption handling

Dependencies

  • Chrome Extension Framework
  • Privacy Control System

Implementation Requirements

  • Programming Language: TypeScript
  • Storage Techniques:
    • Encrypted local storage for sensitive data
    • IndexedDB for larger datasets
    • Cache management for performance
    • Storage quota monitoring

Performance Requirements

  • Fast data access (<50ms for typical operations)
  • Efficient storage space utilization
  • Background synchronization where appropriate

Security Considerations

  • Encryption for all sensitive data
  • Secure key management
  • Data isolation between contexts

Testing Strategy

  • Storage performance testing
  • Encryption/decryption testing
  • Quota limit testing
  • Data integrity testing

4.2 Privacy Control System

Purpose

Enforces privacy guarantees and provides transparency.

Interface

  • External Interfaces:
    • User privacy settings UI
  • Internal Interfaces:
    • Privacy policy enforcement
    • Data transmission control
    • Audit logging

Dependencies

  • Local Storage Manager
  • Background Service Worker
  • All components that handle user data

Implementation Requirements

  • Programming Language: TypeScript
  • Privacy Features:
    • Data handling policy enforcement
    • Transmission blocking for sensitive content
    • Privacy settings management
    • Transparency reporting

Performance Requirements

  • Minimal overhead for privacy checks (<5ms)
  • Real-time policy enforcement

Security Considerations

  • Defense-in-depth approach to privacy
  • Multi-layer verification for data handling
  • Clear user consent for any data collection

Testing Strategy

  • Privacy policy compliance testing
  • Data leakage prevention testing
  • Settings effectiveness testing
  • Transparency report accuracy testing

4.3 Analytics Engine

Purpose

Provides privacy-preserving usage metrics.

Interface

  • External Interfaces:
    • Analytics dashboard UI
  • Internal Interfaces:
    • Usage data collection methods
    • Anonymization pipeline
    • Reporting functions

Dependencies

  • Privacy Control System
  • Local Storage Manager
  • Analytics Dashboard

Implementation Requirements

  • Programming Language: TypeScript
  • Analytics Capabilities:
    • Anonymous usage statistics
    • Differential privacy techniques
    • Local-only processing
    • Aggregated reporting

Performance Requirements

  • Low overhead for metrics collection (<1% CPU)
  • Efficient storage of analytics data

Security Considerations

  • No personally identifiable information collection
  • Data aggregation before any storage
  • User control over analytics participation

Testing Strategy

  • Privacy preservation testing
  • Performance impact testing
  • Accuracy testing for metrics
  • Anonymization effectiveness testing

5. User Interface Components

5.1 Tag Management UI

Purpose

Provides interface for email tagging and organization.

Interface

  • External Interfaces:
    • User interaction events
  • Internal Interfaces:
    • Tag suggestion display
    • Tag application methods
    • Instruction input handling

Dependencies

  • DOM Integration Module
  • Inference Processor
  • Gmail API Client

Implementation Requirements

  • Programming Language: TypeScript, HTML, CSS
  • UI Elements:
    • Tag suggestion panel
    • Natural language instruction input
    • Tag browsing and selection
    • Confidence level indicators
    • Feedback mechanisms

Performance Requirements

  • Rendering in <100ms
  • Smooth animations (60fps)
  • Responsive input handling

Security Considerations

  • Input sanitization
  • No exposure of inference details that might contain email content
  • Clear user control over tagging

Testing Strategy

  • Usability testing
  • Visual regression testing
  • Cross-browser compatibility testing
  • Accessibility testing

5.2 Pattern Visualization

Purpose

Visualizes communication patterns and insights.

Interface

  • External Interfaces:
    • User interaction events
  • Internal Interfaces:
    • Data visualization methods
    • Pattern data access

Dependencies

  • Inference Processor
  • DOM Integration Module
  • Learning Module

Implementation Requirements

  • Programming Language: TypeScript, HTML, CSS
  • Key Libraries: D3.js or similar visualization library
  • Visualization Types:
    • Relationship graphs
    • Time-series analysis
    • Topic clusters
    • Sentiment trends
    • Communication patterns

Performance Requirements

  • Initial rendering <500ms
  • Smooth interactions with large datasets
  • Progressive loading for complex visualizations

Security Considerations

  • Abstracted data visualization without raw content
  • Local-only data processing
  • No exposure of private communication details

Testing Strategy

  • Visual accuracy testing
  • Performance testing with large datasets
  • Usability testing for insight discovery
  • Cross-browser rendering testing

5.3 Search Enhancement

Purpose

Provides advanced search capabilities beyond Gmail’s native search.

Interface

  • External Interfaces:
    • User search input
    • Search results display
  • Internal Interfaces:
    • Query parsing methods
    • Semantic search implementation
    • Results formatting

Dependencies

  • Advanced Gmail API Integration
  • Inference Processor
  • DOM Integration Module

Implementation Requirements

  • Programming Language: TypeScript, HTML, CSS
  • Search Capabilities:
    • Natural language query parsing
    • Semantic search extensions
    • Multi-criteria search
    • Result highlighting
    • Search history management

Performance Requirements

  • Query parsing <100ms
  • Search results display <1s

Security Considerations

  • Secure handling of search criteria
  • Local-only storage of search history
  • No transmission of search patterns

Testing Strategy

  • Search accuracy testing
  • Performance testing with large mailboxes
  • Query parsing robustness testing
  • Results relevance testing

5.4 Response Assistant Interface

Purpose

Supports email response generation and management.

Interface

  • External Interfaces:
    • Gmail compose interface
    • User interaction events
  • Internal Interfaces:
    • Response suggestion methods
    • Style adaptation controls
    • Editing interface

Dependencies

  • Inference Processor
  • DOM Integration Module
  • Learning Module

Implementation Requirements

  • Programming Language: TypeScript, HTML, CSS
  • UI Elements:
    • Suggestion panel with multiple options
    • Tone and style selectors
    • Editing overlay
    • Confidence indicators
    • Feedback controls

Performance Requirements

  • Suggestion generation <2s
  • Seamless integration with Gmail compose
  • Responsive editing experience

Security Considerations

  • No transmission of draft content
  • Clear indication of AI-generated content
  • User control over final message

Testing Strategy

  • Integration testing with Gmail compose
  • Response quality evaluation
  • Editing experience testing
  • Style adaptation testing

5.5 Model Management Interface

Purpose

Enables model discovery, selection, and management.

Interface

  • External Interfaces:
    • User interaction events
  • Internal Interfaces:
    • Model listing and details
    • Selection and configuration methods
    • Status indicators

Dependencies

  • Model Manager
  • Ollama Integration
  • DOM Integration Module

Implementation Requirements

  • Programming Language: TypeScript, HTML, CSS
  • UI Elements:
    • Model browser with filtering
    • Model details panel
    • Download/update controls
    • Hardware compatibility indicators
    • Performance metrics visualization
    • Configuration options

Performance Requirements

  • Interface rendering <300ms
  • Responsive model switching controls
  • Background operations with clear status indication

Security Considerations

  • Verification of model sources
  • Secure model download process
  • Resource protection

Testing Strategy

  • Usability testing for model selection
  • Download reliability testing
  • Status indicator accuracy testing
  • Configuration effectiveness testing

5.6 Advanced Search and Batch Action Interface

Purpose

Provides powerful search capabilities with batch action functionality.

Interface

  • External Interfaces:
    • User interaction events
    • Search input and results display
  • Internal Interfaces:
    • Search execution methods
    • Batch action controls
    • Results management

Dependencies

  • Advanced Gmail API Integration
  • DOM Integration Module
  • Search Enhancement

Implementation Requirements

  • Programming Language: TypeScript, HTML, CSS
  • UI Elements:
    • Natural language search input
    • Structured search builder
    • Results display with selection tools
    • Batch action toolbar
    • Operation progress indicators
    • Result visualizations
    • Search template management

Performance Requirements

  • Interface rendering <300ms
  • Responsive batch operations with progress feedback
  • Support for operating on large result sets

Security Considerations

  • Confirmation for destructive batch operations
  • Clear indication of operation scope
  • Undo capability for batch actions

Testing Strategy

  • Usability testing for complex search building
  • Batch operation reliability testing
  • Progress indicator accuracy testing
  • Undo/redo functionality testing

6. Management Platform Components

6.1 User Account System

Purpose

Manages user identities, authentication, and access.

Interface

  • External Interfaces:
    • Web application UI
    • Authentication providers
  • Internal Interfaces:
    • Account management methods
    • Profile data access
    • Security settings

Dependencies

  • Subscription Management
  • Advanced Configuration Portal
  • Web Application Framework

Implementation Requirements

  • Programming Language: TypeScript, HTML, CSS
  • Backend: FastAPI (Python)
  • Framework: NextJS (React-based)
  • Authentication: OAuth 2.0, multi-factor authentication

Performance Requirements

  • Authentication flows <1s
  • Session management with minimal overhead
  • Responsive account operations

Security Considerations

  • Secure credential handling
  • Protection against common attacks (XSS, CSRF)
  • Privacy-preserving account data management

Testing Strategy

  • Security penetration testing
  • Authentication flow testing
  • Account isolation testing
  • Performance testing under load

6.2 Subscription Management

Purpose

Handles commercial aspects of the service.

Interface

  • External Interfaces:
    • Payment providers APIs
    • Subscription management UI
  • Internal Interfaces:
    • Plan management methods
    • Billing status and history
    • Entitlement verification

Dependencies

  • User Account System
  • Web Application Framework
  • Payment Processing Services

Implementation Requirements

  • Programming Language: TypeScript (frontend), Python (backend)
  • Backend: FastAPI
  • Frontend: NextJS
  • Payment Integrations: Stripe, PayPal, or similar
  • Features:
    • Plan selection and comparison
    • Payment method management
    • Billing history and receipts
    • Upgrade/downgrade flows
    • Trial management
    • Enterprise licensing

Performance Requirements

  • Subscription operations <2s
  • Real-time entitlement verification
  • Reliable payment processing

Security Considerations

  • PCI compliance for payment handling
  • Secure storage of billing information
  • Transparent pricing and terms

Testing Strategy

  • Payment flow testing
  • Subscription state transition testing
  • Entitlement verification testing
  • Upgrade/downgrade path testing

6.3 Advanced Configuration Portal

Purpose

Provides extended configuration capabilities.

Interface

  • External Interfaces:
    • Web application UI
  • Internal Interfaces:
    • Configuration storage and sync
    • Settings validation
    • Device management

Dependencies

  • User Account System
  • Local Storage Manager (for sync)
  • Chrome Extension Framework

Implementation Requirements

  • Programming Language: TypeScript (frontend), Python (backend)
  • Backend: FastAPI with Pydantic schemas
  • Frontend: NextJS
  • Features:
    • Cross-device settings sync
    • Advanced preference management
    • Model configuration
    • Rule builder
    • Backup/restore functionality
    • Usage quota management

Performance Requirements

  • Settings operations <500ms
  • Efficient synchronization across devices
  • Responsive configuration interface

Security Considerations

  • Secure settings storage
  • Settings validation to prevent harmful configurations
  • Clear user control over synchronization

Testing Strategy

  • Sync reliability testing
  • Settings validation testing
  • Cross-device consistency testing
  • Configuration effectiveness testing

6.4 Analytics Dashboard

Purpose

Provides insights into personal usage patterns.

Interface

  • External Interfaces:
    • Web application UI
  • Internal Interfaces:
    • Analytics data retrieval
    • Visualization methods
    • Reporting functions

Dependencies

  • User Account System
  • Analytics Engine
  • Privacy Control System

Implementation Requirements

  • Programming Language: TypeScript (frontend), Python (backend)
  • Backend: FastAPI for analytics data API
  • Frontend: NextJS
  • Visualization Libraries: D3.js, Chart.js, or similar
  • Features:
    • Privacy-preserving usage statistics
    • Productivity metrics
    • Feature utilization insights
    • Time-saving analytics
    • Pattern discovery visualization
    • Personal ROI calculation

Performance Requirements

  • Dashboard loading <1s
  • Responsive visualization interactions
  • Efficient data retrieval for reporting

Security Considerations

  • Privacy-first analytics design
  • No exposure of personally identifiable information
  • Clear explanation of data sources

Testing Strategy

  • Visualization accuracy testing
  • Data integrity verification
  • Privacy preservation testing
  • Performance testing with large datasets

6.5 Support System

Purpose

Provides user assistance and documentation.

Interface

  • External Interfaces:
    • Web application UI
    • Help content management system
  • Internal Interfaces:
    • Knowledge base access
    • Ticket management
    • Community forum integration

Dependencies

  • User Account System
  • Web Application Framework
  • Content Management System

Implementation Requirements

  • Programming Language: TypeScript (frontend), Python (backend)
  • Backend: FastAPI
  • Frontend: NextJS
  • Features:
    • Searchable knowledge base
    • Contextual help integration
    • Ticket creation and tracking
    • Community forum
    • Feature request collection
    • Interactive tutorials and guides

Performance Requirements

  • Help content loading <500ms
    • Search results in <1s
    • Responsive support interfaces

Security Considerations

  • Privacy in support communications
  • Secure handling of support data
  • Clear boundaries for support access

Testing Strategy

  • Help content accuracy testing
  • Search effectiveness testing
  • Support flow usability testing
  • Knowledge base coverage testing

Integration Patterns

This section describes how components interact with each other through well-defined integration patterns:

1. Event-Driven Communication

  • Components communicate through a centralized event bus
  • Events are typed and versioned
  • Loose coupling between components
  • Event replay capabilities for debugging

2. Dependency Injection

  • Components receive dependencies through constructor injection
  • Facilitates testing and component substitution
  • Clear dependency hierarchies

3. Model-View-Controller Pattern

  • UI components follow MVC pattern
  • Models maintain component state
  • Controllers handle business logic
  • Views handle presentation

4. Repository Pattern

  • Data access abstracted through repositories
  • Consistent interface for data operations
  • Caching and optimization at repository level

5. Command Pattern

  • Complex operations encapsulated as commands
  • Support for undo/redo
  • Command composition for complex operations
  • Command logging for debugging

6. Strategy Pattern

  • Interchangeable algorithms implemented as strategies
  • Dynamic strategy selection based on context
  • Facilitates A/B testing of different approaches

7. NextJS-FastAPI Integration

  • NextJS frontend communicates with FastAPI backend via RESTful APIs
  • Pydantic schemas in FastAPI automatically generate TypeScript types for frontend
  • NextJS API routes proxy certain requests to FastAPI backend when needed
  • Server-side rendering in NextJS leverages FastAPI data for initial page loads
  • Authentication flows coordinated between NextJS middleware and FastAPI security
  • Shared validation logic between Pydantic (backend) and Zod/Yup (frontend)
  • API documentation automatically generated from FastAPI OpenAPI specifications

Deployment Considerations

This section outlines considerations for deploying MALENIO components:

1. Chrome Web Store Distribution

  • Extension packaging requirements
  • Review process considerations
  • Update strategy and frequency

2. Ollama Integration

  • Installation and configuration automation
  • Version compatibility management
  • Resource requirement verification

3. Web Platform Deployment

  • NextJS frontend deployment options (Vercel, self-hosted)
  • FastAPI backend deployment with Uvicorn/Gunicorn
  • Docker containerization for consistent environments
  • Database requirements for FastAPI backend components
  • API gateway configuration for routing between services
  • Cloud infrastructure requirements
  • Scaling considerations for both frontend and backend
  • Geographical distribution for low latency

4. Installation Process

  • All-in-one installer requirements
  • Component verification during installation
  • Recovery from failed installations

Appendix A: Interface Definitions

Detailed interface definitions for all component interfaces (API contracts).

Appendix B: Data Schemas

Schemas for all data structures used in component interactions.

Appendix C: Component Diagrams

Visual representations of component relationships and interactions.

Appendix D: Resource Requirements

Detailed resource requirements for each component.

Appendix E: NextJS and FastAPI Technical Specifications

NextJS Implementation Details

Core Framework Features

  • Version: NextJS 14.0+ (with App Router)
  • Rendering Strategy: Hybrid (Server Components + Client Components)
  • Styling Solution: Tailwind CSS with component library
  • State Management:
    • React Context API for local state
    • TanStack Query for server state
    • Zustand for global UI state
  • Form Handling: React Hook Form with Zod validation
  • Routing: Next.js App Router with middleware for authentication
  • Authentication: NextAuth.js integrated with FastAPI backend

Performance Optimizations

  • Image optimization with next/image
  • Font optimization with next/font
  • Streaming and Progressive Rendering
  • Code splitting and lazy loading
  • Edge Runtime for global distribution

Development Tooling

  • TypeScript for type safety
  • ESLint and Prettier for code quality
  • Jest and React Testing Library for testing
  • Storybook for component documentation

FastAPI Implementation Details

Core Framework Features

  • Version: FastAPI 0.100.0+
  • ASGI Server: Uvicorn with Gunicorn for production
  • Authentication: JWT with OAuth2PasswordBearer
  • Data Validation: Pydantic v2 models
  • Database Access: SQLAlchemy 2.0 with async support
  • API Documentation: Automatic Swagger/ReDoc generation
  • Background Tasks: FastAPI background tasks and Celery for longer processes

Performance Optimizations

  • Async endpoints for high concurrency
  • Connection pooling for database operations
  • Caching strategies with Redis
  • Data pagination for large result sets
  • Rate limiting for API protection

Development Tooling

  • Python type annotations throughout
  • Pytest for testing API endpoints
  • Alembic for database migrations
  • Pre-commit hooks for code quality
  • Docker development environment

Integration Points

Data Exchange

  • Pydantic models exported as TypeScript interfaces
  • OpenAPI client generation for frontend
  • Consistent error formatting between layers
  • File upload handling with streaming
  • WebSocket connections for real-time features

Security Measures

  • CSRF protection
  • Rate limiting
  • Input validation on both ends
  • Content Security Policy
  • API scoping and permission management

Monitoring and Observability

  • Integrated logging between NextJS and FastAPI
  • Performance metrics collection
  • Error tracking and reporting
  • User journey tracking
  • Health check endpoints

Conclusion

This Component Specification document provides a comprehensive blueprint for implementing the MALENIO Gmail AI Assistant. The detailed component descriptions, interfaces, and implementation requirements serve as a guide for development teams to build a cohesive and high-performing system.

The selection of NextJS and FastAPI as the core technologies for the web platform components represents a strategic choice that aligns perfectly with MALENIO’s architecture principles:

  1. Performance Efficiency: Both technologies are designed for high performance. NextJS provides optimized rendering strategies while FastAPI is one of the fastest Python web frameworks available.

  2. Developer Experience: The combination offers excellent developer productivity with strong typing support (TypeScript + Python type hints), comprehensive documentation, and modern development patterns.

  3. Type Safety: End-to-end type safety is achieved through Pydantic’s ability to generate TypeScript interfaces from Python models, reducing errors in data exchange.

  4. Scalability: The architecture allows for scaling both horizontally and vertically, with NextJS deployable to edge networks and FastAPI supporting asynchronous request handling.

  5. Security: Built-in security features in both frameworks, along with their mature ecosystems, provide robust protection against common web vulnerabilities.

  6. Documentation: Automatic API documentation generation from FastAPI combined with component documentation from Storybook creates comprehensive technical documentation.

With this technical foundation, MALENIO is well-positioned to deliver a sophisticated Gmail AI Assistant that fulfills its promise of privacy-first, powerful email management with exceptional user experience.

Revision History

Date Version Description Author
2025-03-12 0.1 Initial draft MALENIO Technical Team
2025-03-12 0.2 Updated web platform components to use NextJS and FastAPI stack MALENIO Technical Team