System Requirements Document (SRD)

Project Name: venus-clone

1. Introduction

The venus-clone project aims to replicate the functionality of ChatGPT, a conversational AI system, while tailoring it to meet specific user needs. This document outlines the system requirements for venus-clone, which will serve as a robust, scalable, and user-friendly conversational AI platform.

Moon Light, based in India, envisions this project as a versatile chatbot capable of handling both general-purpose and niche-specific interactions. The system will be designed to support text-based interactions, with potential for future expansion into voice-based features.

2. System Overview

The venus-clone system will be a conversational AI platform built to simulate human-like interactions. It will leverage state-of-the-art AI models to provide accurate, context-aware, and engaging responses. The system will be accessible via web and mobile applications, ensuring a seamless user experience across devices.

The platform will cater to a diverse range of users, including individuals seeking general information, businesses requiring customer support automation, and educators looking for AI-driven learning tools.

Key features include:

• Real-time conversational capabilities.
• Support for multiple languages and locales, with a focus on Indian users.
• Scalable architecture to handle high traffic.
• Modular design for easy integration with third-party tools and APIs.

3. Functional Requirements

Story Points:

• As a User, I should be able to interact with the chatbot via text input.
• As a User, I should receive human-like, context-aware responses.
• As a User, I should be able to switch between multiple languages, including English and Indian regional languages.
• As an Admin, I should be able to monitor and analyze chatbot interactions for quality assurance.
• As an Admin, I should be able to update the chatbot's knowledge base dynamically.
• As a Guest, I should be able to test the chatbot without creating an account.
• As a User, I should be able to save conversation history for future reference.
• As a User, I should be able to provide feedback on the chatbot's responses.

4. User Personas

1. User

• Description: General users interacting with the chatbot for various purposes, such as seeking information, entertainment, or assistance.
• Needs: Accurate, context-aware responses; language flexibility; ability to save conversations.

2. Admin

• Description: System administrators responsible for managing and maintaining the chatbot.
• Needs: Tools for monitoring interactions, updating the knowledge base, and ensuring system performance.

3. Guest

• Description: Unregistered users exploring the chatbot's capabilities.
• Needs: Limited access to test the chatbot's features without account creation.

5. Visuals Colors and Theme

Color Palette:

• Background: #F5F7FA (soft, calming white-blue)
• Surface: #FFFFFF (pure white for cards and input areas)
• Text: #2C3E50 (deep navy for readability)
• Accent: #FF6F61 (vibrant coral for buttons and highlights)
• Muted Tones: #B0BEC5 (soft gray for secondary text and borders)

This palette is designed to evoke a sense of professionalism and approachability, aligning with the project's goal of creating a user-friendly conversational AI.

6. Signature Design Concept

The venus-clone homepage will feature an interactive galaxy map as its centerpiece.

Concept Details:

• Visuals: A dynamic, 3D galaxy where each star represents a feature or section of the chatbot. Users can click on stars to "zoom in" and explore functionalities like language settings, saved conversations, or feedback tools.
• Animations: Stars will twinkle subtly, and constellations will form as users hover over related features.
• Transitions: Smooth zoom-in and zoom-out effects, with a slight parallax shift to create depth.
• Interactions: Clicking on a star will open a modal or navigate to the corresponding section, accompanied by a soft glow animation.
• Color Shifts: The galaxy's background will transition from a deep purple (#2E1A47) to a lighter lavender (#9C89B8) as users interact, creating a sense of exploration and discovery.

This design will make the venus-clone platform instantly memorable and engaging, setting it apart from conventional chatbot interfaces.

7. Non-Functional Requirements

• Performance: The system must handle at least 10,000 concurrent users with minimal latency (<200ms response time).
• Scalability: The architecture should support horizontal scaling to accommodate future growth.
• Security: All user data must be encrypted in transit and at rest, adhering to GDPR and Indian data protection laws.
• Availability: The system should maintain 99.9% uptime.
• Localization: Support for multiple Indian languages, with accurate translations and cultural context.

8. Tech Stack

Frontend:

• React for Web
• React Native for Mobile App

Backend:

• Python
• FastAPI

Database:

• MySQL (with Alembic for migrations)

AI Models:

• GPT 5.4 for user-friendly responses
• Claude 4.6 Opas for academic or coding work
• Gemini 3.1 Pro for friendly responses

AI Tools:

• Litellm for LLM Routing
• Langchain

Orchestration:

• Docker and docker-compose for local development
• Kubernetes for server-side orchestration

9. Assumptions and Constraints

Assumptions:

• Users will primarily interact with the chatbot in English and Indian regional languages.
• The system will initially focus on text-based interactions, with voice features considered for future updates.
• The chatbot will be hosted on a cloud platform to ensure scalability and availability.

Constraints:

• The system must comply with Indian data protection laws.
• Limited initial budget may restrict the use of certain advanced AI models or features.
• The chatbot's knowledge base will require periodic updates to remain relevant and accurate.

10. Glossary

• Chatbot: A software application designed to simulate human-like conversations with users.
• LLM (Large Language Model): Advanced AI models trained on vast datasets to understand and generate human-like text.
• Localization: Adapting the chatbot to support multiple languages and cultural contexts.
• Orchestration: The automated arrangement, coordination, and management of computer systems and services.
• GDPR: General Data Protection Regulation, a legal framework for data protection and privacy in the European Union.