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Kitto AI – Write Better

Django-powered AI writing assistant that generates content with real-time word count and responsive UI.

Django
AWS EC2
RDS
S3
Cloudflare CDN
Kitto AI – Write Better
kitto-ai.md

Kitto AI – Write Better



**Kitto AI** is an advanced AI-powered writing assistant built with **Django** that helps users create high-quality content with intelligent suggestions and real-time feedback. The platform leverages modern AI technologies to enhance the writing experience for content creators, bloggers, and professionals.

🚀 Key Features



• **AI-Powered Content Generation**: Advanced language models provide intelligent writing suggestions and content generation
• **Real-time Word Count**: Live tracking of word count, character count, and reading time estimates
• **Responsive Design**: Fully responsive interface that works seamlessly across all devices
• **Content Optimization**: SEO-friendly content suggestions and readability analysis
• **Multi-format Export**: Export content in various formats including PDF, DOCX, and HTML
• **User Authentication**: Secure user registration and login system
• **Content Management**: Save, edit, and organize your writing projects

🛠️ Technical Implementation



The backend is built with **Django**, providing a robust and scalable foundation for the AI writing assistant. The application is deployed on **AWS EC2** with **RDS** for database management and **S3** for static file storage. **Cloudflare CDN** ensures fast content delivery globally.

The AI integration utilizes state-of-the-art language models to provide contextual writing suggestions and content generation capabilities. The frontend features a clean, intuitive interface built with modern web technologies.

Architecture Highlights:


• **Cloud-native deployment** on AWS infrastructure
• **Auto-scaling capabilities** with EC2 instances
• **Reliable database services** with RDS
• **Global content delivery** via Cloudflare CDN
• **DDoS protection** and security optimization

🏗️ Architecture & Deployment



The system follows a **cloud-native architecture** deployed on AWS infrastructure. The Django application runs on EC2 instances with auto-scaling capabilities, while RDS provides reliable database services. S3 handles static assets and user-generated content, with Cloudflare CDN providing global content delivery and DDoS protection.

💡 Challenges and Solutions



**Challenge**: Optimizing AI response times while maintaining quality
**Solution**: Implemented caching strategies and model optimization techniques to achieve sub-second response times

**Challenge**: Handling concurrent users efficiently
**Solution**: Proper database indexing and connection pooling for optimal performance

Key Features

  • AI-powered content generation
  • Real-time word count tracking
  • Responsive design
  • Content optimization suggestions
  • Multi-format export
  • SEO-friendly content analysis

Technology Stack

Frontend

  • HTML
  • CSS
  • JavaScript
  • Bootstrap

Backend

  • Django
  • Python
  • PostgreSQL

Infrastructure

  • AWS EC2
  • AWS RDS
  • AWS S3
  • Cloudflare CDN

Screenshots

Main writing interface with AI suggestions

Main writing interface with AI suggestions

Content analytics and performance metrics

Content analytics and performance metrics

Export options and format selection

Export options and format selection

Setup & Installation

clone-and-setup.sh
visitor@sagarkundu:~$git clone https://github.com/sa001gar/ai_project_aws_deployment.git
Cloning into 'kitto-ai'...
visitor@sagarkundu:~$cd ai_project_aws_deployment
Command executed successfully
visitor@sagarkundu:~$python -m venv venv
Command executed successfully
visitor@sagarkundu:~$source venv/bin/activate # On Windows: venv\Scripts\activate
Command executed successfully
install-dependencies.sh
visitor@sagarkundu:~$pip install -r requirements.txt
Installing dependencies...
visitor@sagarkundu:~$pip install django python-dotenv boto3
Installing dependencies...
database-setup.sh
visitor@sagarkundu:~$python manage.py makemigrations
Command executed successfully
visitor@sagarkundu:~$python manage.py migrate
Applying database migrations...
visitor@sagarkundu:~$python manage.py createsuperuser
Command executed successfully
run-development-server.sh
visitor@sagarkundu:~$python manage.py collectstatic
Command executed successfully
visitor@sagarkundu:~$python manage.py runserver
Starting development server...Server running at http://127.0.0.1:8000/
# Server running at http://127.0.0.1:8000/