Skip to main content

Software Design Document (SDD)

Executive Summary​

This Software Design Document (SDD) outlines the design and architecture of a generative UI system that utilizes AI agents to build personalized, dynamic dashboards in real-time. The system leverages the AG UI protocol, Copilot Kit, and Pydantic AI to enable this advanced personalization and real-time generation of user interfaces.

The key features of this system include:

  • Generative UI: AI agents dynamically generate the entire layout and components of the dashboard based on user preferences and data.
  • Personalization: The AI agents build a personalized dashboard tailored to the individual user's needs and interests.
  • Real-time Rendering: The dashboard is generated and updated in real-time, providing a seamless and responsive user experience.
  • Extensible Architecture: The system is designed to be agnostic to the specific UI generation approach, allowing for integration with various generative UI technologies.

System Overview​

The generative UI system is designed to create personalized, dynamic dashboards for users in real-time. The system consists of the following key components:

  1. AI Agents: The AI agents are responsible for analyzing user data, preferences, and research to determine the optimal layout, components, and content for the user's dashboard.
  2. AG UI Protocol: The AG UI protocol is used to establish a communication channel between the AI agents and the front-end UI framework, enabling the real-time exchange of UI configurations and updates.
  3. Copilot Kit: Copilot Kit is the front-end framework used to render the dynamically generated UI components and layouts.
  4. Pydantic AI: Pydantic AI is utilized to define the data models and schemas for the UI configurations and other system-related data.

Architecture Design​

The architecture of the generative UI system is designed to be modular and scalable, allowing for easy integration of new technologies and components. The main components and their interactions are depicted in the following diagrams:

System Architecture Diagram​

System Architecture Diagram

The System Architecture Diagram illustrates the high-level components of the generative UI system and their interactions. The AI Agents communicate with the AG UI Protocol to send UI configurations, which are then rendered by the Copilot Kit front-end framework.

Data Flow Diagram​

Data Flow Diagram

The Data Flow Diagram shows the flow of data within the system, including the exchange of UI configurations between the AI Agents and the Copilot Kit front-end, as well as the use of Pydantic AI for data modeling and validation.

Sequence Diagram​

Sequence Diagram

The Sequence Diagram depicts the interactions between the key components of the system, including the AI Agents, AG UI Protocol, and Copilot Kit, during the process of generating and rendering the personalized dashboard.

Component Design​

The generative UI system is composed of the following key components:

  1. AI Agents:

    • Responsible for analyzing user data and preferences to determine the optimal dashboard configuration.
    • Utilizes machine learning and data-driven algorithms to generate personalized UI layouts and component selections.
    • Communicates with the AG UI Protocol to send the generated UI configurations.

  2. AG UI Protocol:

    • Provides a standardized communication protocol for exchanging UI configurations between the AI Agents and the front-end.
    • Supports various generative UI approaches, including static, open-ended, and declarative UI generation.
    • Ensures real-time synchronization between the AI Agents and the front-end.

  3. Copilot Kit:

    • Front-end framework responsible for rendering the dynamically generated UI components and layouts.
    • Provides a flexible and extensible architecture to support different types of generative UI configurations.
    • Integrates with the AG UI Protocol to receive and render the UI configurations sent by the AI Agents.

  4. Pydantic AI:

    • Utilized for defining the data models and schemas for the UI configurations and other system-related data.
    • Ensures data validation and consistency throughout the system.
    • Facilitates the exchange of data between the AI Agents and the Copilot Kit front-end.

Data Design​

The generative UI system relies on the following key data structures and models:

  1. UI Configuration Model:

    • Defined using Pydantic AI
    • Represents the layout, components, and other properties of the personalized dashboard
    • Includes information such as component types, sizes, positions, and any necessary data for rendering

  2. User Preference Model:

    • Defined using Pydantic AI
    • Captures the user's preferences, interests, and other relevant data used by the AI Agents for personalization

  3. Telemetry Data Model:

    • Defined using Pydantic AI
    • Collects and stores user interactions and usage data to enable continuous improvement of the AI Agents' personalization algorithms

Interface Design​

The generative UI system provides the following interfaces:

  1. AG UI Protocol API:

    • Defines the communication interface between the AI Agents and the Copilot Kit front-end
    • Supports the exchange of UI configurations and real-time updates
    • Allows for integration with various generative UI technologies

  2. Copilot Kit UI Components:

    • Provides a set of flexible and extensible UI components that can be dynamically rendered based on the AI Agents' configurations
    • Enables the front-end to adapt to the changing UI layouts and component selections

  3. Pydantic AI Data Models:

    • Exposes the data models and schemas used throughout the system
    • Facilitates the exchange of data between the AI Agents and the front-end
    • Ensures data validation and consistency

Security Considerations​

The generative UI system incorporates the following security measures:

  1. Data Encryption:

    • All communication between the AI Agents and the Copilot Kit front-end is encrypted using industry-standard protocols (e.g., TLS/SSL).
    • User data and preferences are stored and transmitted securely.

  2. Access Control:

    • The system implements role-based access control to limit access to sensitive data and system functionalities.
    • Only authorized users and AI Agents are granted the necessary permissions to interact with the system.

  3. Input Validation:

    • The Pydantic AI data models enforce strict validation of all input data, including the UI configurations generated by the AI Agents.
    • This helps mitigate the risk of injection attacks and other data-related vulnerabilities.

  4. Logging and Monitoring:

    • The system maintains comprehensive logs of all user interactions, system events, and AI Agent activities.
    • Continuous monitoring and analysis of these logs help detect and respond to any suspicious or malicious activities.

  5. Secure Deployment:

    • The system is deployed in a secure, scalable, and fault-tolerant infrastructure, following best practices for cloud-native applications.
    • Regular security audits and updates are performed to address any vulnerabilities or emerging threats.

By incorporating these security measures, the generative UI system ensures the confidentiality, integrity, and availability of user data and system functionality.