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πŸ¦„ Unicorn.Rentals - AWS Bedrock Hackathon 2025

AWS Cloud Istanbul Bedrock Hackathon 2025 Submission

A magical AI-powered healthcare system for mythical creatures, built with Amazon Bedrock and Streamlit. This project demonstrates advanced AI capabilities including multimodal analysis, knowledge base integration, and creative content generation.

🌟 Project Overview

Unicorn.Rentals is a comprehensive healthcare platform for mythical creatures that leverages Amazon Bedrock's powerful AI models to provide:

  • Health Complaint Analysis: AI-powered diagnosis of unicorn health issues
  • Medical Knowledge Base: RAG-powered medical information system
  • Multimodal AI Oracle: Text and image generation capabilities

πŸ—οΈ Architecture

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”    β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚   Streamlit     β”‚    β”‚  Amazon Bedrock  β”‚    β”‚   Amazon S3     β”‚
β”‚   Frontend      │◄──►│                  │◄──►│ Knowledge Base  β”‚
β”‚                 β”‚    β”‚  β€’ Nova Lite     β”‚    β”‚                 β”‚
β”‚  β€’ UniSum       β”‚    β”‚  β€’ Nova Pro      β”‚    β”‚ Medical Files   β”‚
β”‚  β€’ WisdomCare   β”‚    β”‚  β€’ Nova Canvas   β”‚    β”‚ β€’ Anatomy       β”‚
β”‚  β€’ Mystic Oracleβ”‚    β”‚  β€’ Titan Models  β”‚    β”‚ β€’ Ailments      β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜    β”‚  β€’ Claude 3      β”‚    β”‚ β€’ Protocols     β”‚
                       β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜    β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

πŸš€ Features

1. 🩺 UniSum - Health Complaint Analyzer

  • PDF Processing: Extract text from medical transcripts
  • AI Analysis: Use Nova Lite for symptom analysis and severity assessment
  • Report Generation: Generate comprehensive veterinary reports with Nova Pro
  • Triage System: Automatic urgency classification (Low/Medium/High/Emergency)

2. 🧠 WisdomCare - Medical Knowledge Base

  • RAG Implementation: Retrieval-Augmented Generation with Bedrock
  • S3 Integration: Automated medical knowledge upload
  • Multi-Model Support: Nova Lite, Nova Pro, and Claude 3 Haiku
  • Interactive Queries: Natural language medical consultations

3. 🎨 Mystic Oracle - AI Content Generation

  • Text Generation: Multiple model support (Nova, Titan, Claude, Llama)
  • Image Creation: Nova Canvas, Stable Diffusion, Titan Image Generator
  • Model Access Checker: Real-time model availability verification
  • Multimodal Capabilities: Combined text and image generation

πŸ› οΈ Technology Stack

  • Frontend: Streamlit
  • AI/ML: Amazon Bedrock
    • Amazon Nova Lite (multimodal analysis)
    • Amazon Nova Pro (advanced text generation)
    • Amazon Nova Canvas (image generation)
    • Amazon Titan Text & Image models
    • Anthropic Claude 3 models
    • Meta Llama models
  • Storage: Amazon S3
  • Knowledge Base: Amazon Bedrock Knowledge Bases with Titan Embeddings V2
  • Language: Python 3.8+
  • Libraries: boto3, streamlit, PyPDF2, Pillow

πŸ“‹ Prerequisites

  1. AWS Account with appropriate permissions
  2. Amazon Bedrock Model Access:
    • Amazon Nova Lite (amazon.nova-lite-v1:0)
    • Amazon Nova Pro (amazon.nova-pro-v1:0)
    • Amazon Nova Canvas (amazon.nova-canvas-v1:0)
    • Amazon Titan Text Embeddings V2
    • Other models as needed
  3. Python 3.8+
  4. AWS CLI configured with appropriate credentials

πŸš€ Quick Start

1. Clone the Repository

git clone https://github.com/ilkan/aws-cloud-istanbul-bedrock-hackathon-2025.git
cd aws-cloud-istanbul-bedrock-hackathon-2025

2. Install Dependencies

pip install streamlit boto3 PyPDF2 Pillow pandas

3. Configure AWS Credentials

aws configure
# Enter your AWS Access Key ID, Secret Access Key, and region (us-east-1)

4. Enable Bedrock Models

  1. Go to AWS Bedrock Console
  2. Navigate to Model access under Bedrock configurations
  3. Click Modify model access
  4. Enable required models:
    • βœ… Amazon Nova Lite
    • βœ… Amazon Nova Pro
    • βœ… Amazon Nova Canvas
    • βœ… Amazon Titan Text Embeddings V2
    • βœ… Other models as needed
  5. Submit the request

5. Run the Applications

UniSum - Health Analyzer

cd environment/GameDay/ml_repo
streamlit run 1_UniSum.py

WisdomCare - Knowledge Base

cd environment/GameDay/ml_repo
streamlit run pages/2_WisdomCare.py

Mystic Oracle - AI Content Generator

cd environment/GameDay/mystic_code/mystic_code
streamlit run bedrock_app_st.py

πŸ“– Usage Guide

UniSum Health Analyzer

  1. Upload the provided transcript1.txt as a PDF
  2. Click Analyze Health Complaint to get AI-powered diagnosis
  3. Generate a comprehensive veterinary report
  4. Review triage recommendations

WisdomCare Knowledge Base

  1. Create an S3 bucket for medical knowledge
  2. Upload sample medical files
  3. Create a Bedrock Knowledge Base in the AWS Console
  4. Enter the Knowledge Base ID in the app
  5. Ask medical questions and get AI-powered answers

Mystic Oracle

  1. Choose between text generation, image creation, or both
  2. Select your preferred AI model
  3. Enter prompts and generate magical content
  4. Download generated images

🎯 Hackathon Highlights

Innovation Points

  • Multimodal AI: Combines text, image, and document processing
  • RAG Implementation: Advanced knowledge retrieval system
  • Model Diversity: Utilizes multiple Bedrock models for different tasks
  • Real-world Application: Practical healthcare use case with whimsical twist
  • User Experience: Intuitive Streamlit interface with magical theming

Technical Achievements

  • PDF Processing: Automated transcript extraction and analysis
  • Dynamic Model Selection: Runtime model availability checking
  • Error Handling: Comprehensive error management and user guidance
  • Scalable Architecture: Modular design for easy extension

πŸ“ Project Structure

aws-cloud-istanbul-bedrock-hackathon-2025/
β”œβ”€β”€ README.md
β”œβ”€β”€ environment/
β”‚   └── GameDay/
β”‚       β”œβ”€β”€ ml_repo/
β”‚       β”‚   β”œβ”€β”€ 1_UniSum.py              # Health complaint analyzer
β”‚       β”‚   β”œβ”€β”€ pages/
β”‚       β”‚   β”‚   └── 2_WisdomCare.py      # Medical knowledge base
β”‚       β”‚   └── transcript1.txt          # Sample medical transcript
β”‚       └── mystic_code/
β”‚           └── mystic_code/
β”‚               └── bedrock_app_st.py    # AI content generator
β”œβ”€β”€ data/                                # Sample data files
β”œβ”€β”€ logs/                               # Application logs
└── .kiro/                              # IDE configuration

πŸ”§ Configuration

Environment Variables

export AWS_DEFAULT_REGION=us-east-1
export AWS_PROFILE=your-profile-name  # Optional

Model Configuration

The applications automatically detect available models and provide guidance for enabling access to required models.

🎨 Sample Use Cases

  1. Emergency Triage: Analyze urgent unicorn health complaints
  2. Medical Research: Query comprehensive medical knowledge base
  3. Content Creation: Generate magical artwork and stories
  4. Educational Tool: Learn about AI model capabilities

πŸ† Awards & Recognition

This project was developed for the AWS Cloud Istanbul Bedrock Hackathon 2025, showcasing:

  • Advanced Amazon Bedrock integration
  • Creative AI applications
  • Practical problem-solving with whimsical presentation
  • Multi-model AI orchestration

🀝 Contributing

This is a hackathon project, but contributions and improvements are welcome!

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Submit a pull request

πŸ“„ License

This project is licensed under the MIT License - see the LICENSE file for details.

πŸ™ Acknowledgments

  • AWS Bedrock Team for providing powerful AI models
  • AWS Cloud Istanbul for hosting the hackathon
  • Streamlit for the excellent web framework
  • The magical unicorn community for inspiration πŸ¦„

πŸ“ž Contact

Team: Unicorn.Rentals Development Team
Hackathon: AWS Cloud Istanbul Bedrock Hackathon 2025
Repository: GitHub


Built with ❀️ and a touch of magic during the AWS Bedrock Hackathon 2025 ✨

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