InkSight: AI-Powered Mathematical Recognition & Document Analysis

Overview

InkSight is a microservices-based application that combines intelligent mathematical expression recognition and document analysis capabilities. The system utilizes Google's Gemini API for mathematical expression interpretation and Claude AI for document summarization.

Features

• Real-time handwritten mathematical expression recognition
• Interactive drawing canvas with color options
• Document upload and analysis with comprehensive summarization
• Microservices architecture for scalability
• Kubernetes orchestration with automated scaling
• CI/CD pipeline with Jenkins
• Secure configuration management with Ansible Vault

Architecture

The application consists of four microservices:

• API Gateway: Routes requests and handles service orchestration
• Calculator Service: Processes mathematical expressions using Gemini AI
• Document Service: Analyzes documents using Claude AI
• Frontend Service: Provides user interface and drawing capabilities

Technologies Used

• Backend: Python, Flask
• Frontend: HTML, CSS, JavaScript
• AI/ML: Google Gemini API, Anthropic Claude API
• DevOps: Docker, Kubernetes, Jenkins, Ansible
• Version Control: Git, GitHub

Setup and Installation

1. Clone the repository

git clone https://github.com/yourusername/InkSight.git
cd InkSight

2. Build Docker images

docker-compose build

3. Deploy to Kubernetes

ansible-playbook -i inventory ansible/deploy.yml --ask-vault-pass

Environment Variables

Create a .env file with:

GEMINI_API_KEY=your_gemini_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key
SECRET_KEY=your_secret_key

Directory Structure

InkSight/
├── api-gateway/
├── calculator-service/
├── document-service/
├── frontend-service/
├── k8/
├── ansible/
├── jenkins/
└── docker-compose.yml

API Documentation

Calculator Service

• POST /calculate: Processes mathematical expressions
• GET /health: Service health check

Document Service

• POST /upload: Analyzes uploaded documents
• GET /health: Service health check

CI/CD Pipeline

The project uses Jenkins for continuous integration and deployment:

1. Automatic builds on code push
2. Docker image creation and push
3. Kubernetes deployment with rolling updates
4. Automated testing and verification

Monitoring and Logging

• Kubernetes pod health monitoring
• Service-level logging with date-based organization
• Performance metrics tracking
• Auto-scaling based on CPU usage

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit changes
4. Push to the branch
5. Open a pull request

License

This project is licensed under the MIT License

Authors

• Dev Shinde
• Mahima

Acknowledgments

• Google Cloud Platform for Gemini API
• Anthropic for Claude API
• Open source community

Contact

For any queries, reach out to shindedev64@gmail.com