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https://github.com/redx94/quantumai

🚀 QuantumAI merges Quantum Computing with Artificial Intelligence to revolutionize machine learning, cryptography, and optimization. Leveraging quantum superposition, entanglement, and hybrid AI models, this project pushes the boundaries of computational intelligence. ⚡ Next-gen AI meets quantum power! 💡
https://github.com/redx94/quantumai

ai-and-quantum hybrid-ai-quantum qiskit qiskit-ai qml quantum-algorithms quantum-cryptography quantum-machine-learning quantum-neural-networks quantum-optimization quantumai

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🚀 QuantumAI merges Quantum Computing with Artificial Intelligence to revolutionize machine learning, cryptography, and optimization. Leveraging quantum superposition, entanglement, and hybrid AI models, this project pushes the boundaries of computational intelligence. ⚡ Next-gen AI meets quantum power! 💡

Awesome Lists containing this project

README 

          
# QuantumAI Framework



Enterprise-grade framework for quantum-enhanced AI and AGI, integrating next-generation quantum computing with advanced machine intelligence.



## Vision



QuantumAI aims to create a seamless fusion between quantum computing and deep learning to unlock AI capabilities beyond classical limitations, while maintaining industrial-grade security and ethical considerations.



## Core Features



- Quantum-Classical Hybrid Neural Networks

- Multi-Modal Learning with Quantum Enhancement

- Post-Quantum Cryptography Security

- AGI Development Framework

- Hardware Abstraction Layer for Multiple Quantum Backends



## Installation



```bash

poetry install

```



## Quick Start



```python

from quantumai.q_fabric import QuantumCircuit

from quantumai.ai_engine import HybridNetwork



# Initialize quantum circuit

qc = QuantumCircuit()



# Create hybrid network

model = HybridNetwork()

```



## Documentation



See the `docs/` directory for detailed documentation.



## Security



All AGI components are sandboxed and require cryptographic signatures for execution.



## License



Proprietary - All Rights Reserved



# QuantumAI 🧠⚛️

> The future of AI is Quantum - Core framework combining Quantum Computing and AI






![QuantumAI Banner](assets/images/banner.jpeg)



[![License](https://img.shields.io/badge/License-QPL%20v1.1-red)](LICENSE.md)

[![Python](https://img.shields.io/badge/Python-3.9%2B-blue)](#prerequisites)

[![Status](https://img.shields.io/badge/Status-Active-brightgreen)](#status)






## Directory Structure



```

app/

    api/        # FastAPI endpoints

    core/       # Core quantum computing logic

    dao/        # Data access layer

    models/     # Data models

    services/   # Business logic

    utils/      # Helpers and utilities

contracts/      # Smart contracts for licensing

docs/          # Documentation

frontend/      # React-based UI

notebooks/     # Jupyter notebooks

scripts/       # Utility scripts  

src/           # Core quantum-AI implementation

test/          # Test suite

```



## Quick Links

- [API Documentation](docs/api/README.md)

- [Development Guide](docs/guides/development.md)

- [Chat Interface](frontend/README.md)

- [License System](contracts/README.md)



---



## 🚀 About QuantumAI  

QuantumAI is a **proprietary AI-Quantum computing framework** that enhances **machine learning algorithms with quantum-powered optimizations**. This project is **designed for serious researchers, AI engineers, and enterprises** seeking to leverage **quantum-enhanced AI models**.  



**🔒 Commercial usage requires a paid license.** See **[LICENSE.md](LICENSE.md)** for terms.  



---



## ✨ Key Features  



✅ **Quantum-enhanced neural networks** – Unlock AI capabilities beyond classical computing.  

✅ **Hybrid Classical-Quantum Optimization** – Combines classical deep learning with quantum optimization.  

✅ **Quantum Feature Mapping** – Transform classical data into quantum states for superior efficiency.  

✅ **Multi-Quantum Hardware Support** – Compatible with **IBM Q, Rigetti, Google Quantum AI, IonQ,** and more.  

✅ **FastAPI-Powered API** – Expose quantum models via RESTful API & WebSockets.  

✅ **Built-in Quantum ML Benchmarking** – Evaluate classical vs. quantum performance.  



---



## 🛠️ Prerequisites  



To run QuantumAI, ensure you have the following:  



### **Required**  

🔹 Python **3.9+**  

🔹 **Poetry** (Dependency manager)  

🔹 **gcc/g++** (For compiling core components)  



### **Optional (For CUDA Acceleration)**  

🔹 **NVIDIA CUDA** – For faster deep learning computations  

🔹 **cuQuantum SDK** – Optimized quantum circuit simulations  



### **Important Version Constraints**  

- `numpy == 1.23.5`  

- `pennylane == 0.31.0`  



---



## 🔧 Installation  



### **1️⃣ Install System Dependencies** (Ubuntu/Debian)  



```bash

sudo apt-get update

sudo apt-get install python3-dev build-essential gcc g++

```



### **2️⃣ Install QuantumAI with Poetry**  



```bash

poetry config virtualenvs.in-project true

poetry install --no-cache

```



#### **🛠️ Troubleshooting: NumPy Issues?**  



```bash

poetry run pip install --no-cache-dir numpy==1.23.5

poetry install

```



---



## 🚀 Usage  



### **Start the API Server**  



```bash

poetry run uvicorn quantum_ai.api.main:app --reload

```



### **Run Quantum Workloads**  



```python

from quantum_ai.circuits import QuantumCircuit

qc = QuantumCircuit()

qc.run()

```



---



## 🧪 Testing  



Run the test suite:  



```bash

poetry run pytest

```



---



## 🏗️ Architecture  



QuantumAI follows a **modular architecture**, ensuring extensibility and seamless integration of **quantum and classical AI models**.  



📂 **`quantum_ai/circuits/`**  

  - Gate-based **quantum circuits**  

  - Variational **quantum algorithms**  



📂 **`quantum_ai/api/`**  

  - **FastAPI**-based REST API  

  - WebSocket support for **real-time quantum inference**  



📂 **`quantum_ai/embeddings/`**  

  - **Quantum Feature Mapping**  

  - Hybrid **classical-quantum embeddings**  



📂 **`quantum_ai/training/`**  

  - **Quantum-enhanced neural networks**  

  - **Hybrid QML optimizers**  



---



## 🔥 Roadmap  



🚀 **Q1 2025:** **Quantum GANs** – Generative adversarial networks powered by quantum sampling.  

🚀 **Q2 2025:** **Quantum NLP** – Explore quantum-enhanced **natural language processing**.  

🚀 **Q3 2025:** **Federated Quantum Learning** – Secure, decentralized AI training.  



[📜 Full Roadmap](docs/roadmap.md)  



---



## 🤝 Contributing  



🔹 **Fork the Repository**  

🔹 **Create a Feature Branch**  

🔹 **Run Tests Before Submitting PRs**  

🔹 **Submit a Pull Request with Detailed Notes**  



---



## 📜 Documentation  



📘 **API Docs:** `http://localhost:8000/docs`  

📘 **[Architecture Overview](docs/architecture.md)**  

📘 **[Development Guide](docs/development.md)**  



---



## 🔒 License  



QuantumAI is licensed under the **QuantumAI Proprietary License (QPL v1.1)**.  



⚠️ **This software is NOT open-source**. Commercial use requires a **paid license**.  



📜 **Read Full Terms:** [LICENSE.md](LICENSE.md)  



---



## 🚀 Support & Contact  



📧 **Email:** quantascriptor@gmail.com  

🌎 **Website:** [quantum.api](https://quantum.api)    



---



# QuantumAI Chat Interface



A next-generation chat interface with quantum computing capabilities.



## Features



- 🚀 Real-time quantum-enhanced chat responses

- ✨ Animated message transitions

- 📝 Markdown support in messages

- 🎵 Sound effects for interactions

- 👍 Message reactions

- ⌨️ Typing indicators

- 📱 Responsive design

- 🎨 Dark mode interface



## Setup



1. Install dependencies:

```bash

npm install

# or

yarn install

```



2. Install required packages:

```bash

npm install framer-motion react-markdown react-icons use-sound axios

```



3. Add sound effects:

- Create a `public` folder in your project root

- Add `message-sound.mp3` to the `public` folder



4. Start the development server:

```bash

npm run dev

# or

yarn dev

```



## Environment Variables



Create a `.env` file in the root directory:



```env

REACT_APP_API_URL=your_api_url

```



## Tech Stack



- React with TypeScript

- Framer Motion for animations

- React Markdown for message formatting

- Use-Sound for audio effects

- Axios for API calls



## Contributing



1. Fork the repository

2. Create your feature branch (`git checkout -b feature/amazing-feature`)

3. Commit your changes (`git commit -m 'Add some amazing feature'`)

4. Push to the branch (`git push origin feature/amazing-feature`)

5. Open a Pull Request



---



# QuantumAI License Management System



A blockchain-based licensing system for AI model access control and monetization.



## Overview



The QuantumAI License Management System provides:

- Time-based access control for AI models

- Automated license validation and enforcement

- Usage-based billing and royalty collection

- Programmatic access revocation

- Transparent transaction history



## Technical Architecture



### Smart Contract Components



1. **License Token (ERC-1155)**

   - Represents active license ownership

   - Includes metadata about license terms

   - Non-transferable implementation



2. **Revenue Sharing (ERC-2981)**

   - Automated royalty distribution

   - Configurable revenue split

   - Per-transaction enforcement



3. **Access Control**

   - Time-based validation

   - Grace period handling

   - Blacklist functionality



## Implementation Guide



### Contract Deployment



```javascript

const contract = await QuantumAILicense.deploy(

  licenseFee,    // Base fee in wei

  royaltyRate    // Percentage (1-100)

);

```



### License Management



```javascript

// Purchase license

await contract.purchaseLicense(duration, { value: fee });



// Validate license

const isValid = await contract.hasValidLicense(address);



// Revoke access

await contract.revokeLicense(address);

```



### API Integration



```python

from web3 import Web3

from quantum_ai.licensing import LicenseValidator



def verify_access(user_address: str) -> bool:

    return await LicenseValidator.check_license(user_address)

```



## Security Considerations



- Immutable license records

- Cryptographic access verification

- Automated compliance enforcement

- Transparent audit trail



## Technical Documentation



- [Smart Contract Reference](docs/contract-reference.md)

- [API Integration Guide](docs/api-integration.md)

- [Security Model](docs/security.md)



## License



Commercial use requires a valid on-chain license. See [LICENSE.md](LICENSE.md).



# QuantumAI



A cutting-edge framework integrating Quantum Computing with Artificial Intelligence and AGI systems.



## Project Structure



```

📂 q_fabric/      - Quantum computation modules and simulators

📂 ai_engine/     - AI models and quantum-enhanced layers

📂 security/      - Cryptographic and quantum-secure authentication

📂 docs/          - Documentation and API references

📂 tests/         - Unit tests for all components

```



## Features



- Universal quantum backend wrapper (Qiskit, PennyLane, Cirq, Braket)

- Quantum-enhanced neural networks

- Post-quantum cryptography

- AGI governance system

- Real-time quantum hardware execution

- Quantum-safe model protection



## Installation



```bash

pip install quantum-ai

```



## Quick Start



```python

from quantum_ai import QuantumNeuralNetwork

from quantum_ai.security import QUANTUM_SHIELDWALL



# Initialize a quantum-enhanced neural network

qnn = QuantumNeuralNetwork()

```



## Documentation



Visit [docs/](docs/) for complete documentation.



## Security



All AI models are protected by QUANTUM_SHIELDWALL™ technology.



## License



<<<<<<< HEAD

See the LICENSE file for details.

=======

MIT License



## Development Best Practices



### Code Style

- Use type hints for all Python code

- Follow PEP 8 guidelines

- Document all public functions and classes

- Use meaningful variable names



### Testing Standards

- Write unit tests for all new features

- Maintain minimum 80% code coverage

- Include integration tests for API endpoints

- Test quantum circuits with simulation backends



### Performance Guidelines

- Profile quantum circuits before deployment

- Optimize classical-quantum interfaces

- Minimize quantum gate depth where possible

- Cache intermediate results when appropriate



### Security Requirements

- All PRs must pass security scan

- Implement access controls for quantum resources

- Follow quantum-safe cryptography practices

- Regular security audits required

>>>>>>> 5c96586 (refactoring)