System Requirements Document (SRD)

1. Introduction

This document outlines the system requirements for the development of a software solution. It includes functional and non-functional requirements, user personas, visual design guidelines, technical specifications, assumptions, and constraints. The goal is to ensure clarity and alignment among stakeholders for the successful implementation of the system.

2. System Overview

The system is designed to provide users with a robust and user-friendly platform for retrieving live commodity prices using an agentic AI module. The solution will cater to different user personas, ensuring accessibility and functionality for all intended users. The system will leverage modern technologies and AI capabilities to deliver accurate and timely information.

3. Functional Requirements as Story Points

• As User, I should be able to retrieve live commodity prices using an agentic AI module.
• As Admin, I should be able to monitor and manage the AI module's performance and data accuracy.
• As Developer, I should be able to test and refine the AI module at a developer level, ensuring it is functional but not yet production-ready.

4. User Personas

1. User

A general user who interacts with the system to retrieve live commodity prices. They require a simple and intuitive interface to access accurate data.

2. Admin

An administrator responsible for overseeing the system's operations, ensuring data accuracy, and managing the AI module's performance.

3. Developer

A technical user who works on building, testing, and refining the AI module. They focus on ensuring the module is functional at a developer level, preparing it for potential production use.

5. Visuals Colors and Theme

The system will adopt a professional and modern theme with the following color palette:

• Primary Color: Deep Blue (#003366) for headers and navigation.
• Secondary Color: Light Gray (#F2F2F2) for backgrounds.
• Accent Color: Bright Yellow (#FFD700) for highlights and actionable buttons.
• Text Color: Black (#000000) for readability.
• Error Messages: Red (#FF0000) for warnings and errors.

The theme will emphasize clarity, professionalism, and ease of use.

6. Non-Functional Requirements

• The system should provide responses to user queries within 2 seconds.
• The AI module should maintain an accuracy rate of at least 95% for live commodity prices.
• The system should be scalable to handle up to 10,000 concurrent users.
• The system should ensure data security and comply with relevant regulations (e.g., GDPR).
• The interface should be responsive and accessible on both web and mobile platforms.

7. Tech Stack

Frontend

• React for Web
• React Native for mobile app

Backend

• Python
• FastAPI

Database

• MySQL or MariaDB (preferred for relational data)
• Alembic for database migrations

AI Models

• GPT 5.2 for user-friendly responses
• Claude 4.5 Opas for academic or coding work
• Gemini 3 Pro for friendly responses

AI Tools

• Litellm for LLM Routing
• Langchain

Local Orchestration

• Docker
• docker-compose

Server-side Orchestration

• Kubernetes

8. Assumptions and Constraints

Assumptions

• Users will have access to the internet to interact with the system.
• The AI module will be trained on reliable and up-to-date commodity price data sources.
• Developers will have access to necessary APIs and tools for testing and refining the module.

Constraints

• The system will not be production-ready initially; it will be developed at a developer level.
• The AI module's accuracy depends on the quality and timeliness of the data sources.
• The system must comply with data privacy and security regulations.

9. Glossary

• Agentic AI Module: An AI system capable of autonomous decision-making and retrieving specific data (e.g., live commodity prices).
• Commodity Prices: The current market value of goods such as gold, oil, and agricultural products.
• Developer Level: A stage of development focused on testing and refining functionality, not yet ready for production use.
• Production Level: A stage of development where the system is fully operational and ready for end-users.
• LLM Routing: The process of directing queries to the appropriate large language model for optimal responses.

This document has been updated to include the new functional requirement for developing an agentic AI module to retrieve live commodity prices.