Architecture

System Design and Architecture

The architecture of the LLM Token Analytics Library is designed to facilitate modularity and reusability. It consists of core components that interact seamlessly to provide a comprehensive analytics solution.

Core Components and Their Interactions

• API Server: A Flask-based server that handles incoming requests for running simulations and data analysis.
• Simulation Engine: The core logic that executes various pricing simulations.
• Data Collection Module: Interfaces with LLM providers to gather usage data.
• Visualization Module: Generates visual representations of the simulation results and usage data.

Technology Stack and Dependencies

• Programming Languages: Python, JavaScript
• Frameworks: Flask (for API server), Dash (for dashboard visualization)
• Data Processing: Pandas, NumPy
• Statistical Analysis: SciPy, Statsmodels
• Visualization: Plotly, Matplotlib, Seaborn
• Databases: Supports local file-based storage; can be extended for cloud storage

Design Patterns Used

• MVC (Model-View-Controller): Separates data handling, user interface, and application logic for cleaner code organization.
• Singleton: Used for managing API client instances to ensure a single point of access.