WholeBrainedIntelligence (WBI)

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Whole-Brained Intelligence (WBI) - Version 3.0.0

Whole-Brained Intelligence (WBI) integrates advanced technologies like Quantum Neural Networks, Neuromorphic Computing, Advanced NLP, and Autonomous Learning.

Features

• Quantum Neural Networks (QNN)
• Neuromorphic Computing
• Advanced NLP
• Autonomous Learning and Adaptation
• Ethical and Secure AI

Getting Started

Prerequisites

• Python 3.8+
• pip

Installation

1. Clone the repository:

 git clone https://github.com/QuantaScriptor/WholeBrainedIntelligence_WBI.git
 cd WholeBrainedIntelligence_WBI

2. Create and activate a virtual environment:

python3 -m venv venv
source venv/bin/activate  # On Windows use `venv\\Scripts\\activate`

3. Install dependencies:

pip install -r requirements.txt

Usage

Run the main scripts:

from opensource_scripts.neurosymbolic_ai import hybrid_model as neurosymbolic_hybrid_model
from opensource_scripts.quantum_integration import hybrid_model as quantum_hybrid_model

inputs = [0.5, 0.6]
neural_output, symbolic_output = neurosymbolic_hybrid_model(inputs)
print(f"Neural network output: {neural_output}")
print(f"Symbolic reasoning output: {symbolic_output}")

inputs = np.array([0.5, 0.6])
result = quantum_hybrid_model(inputs)
print(f"Quantum model output: {result}")

Testing

1. Run tests using pytest:

pytest --cov=opensource_scripts tests/

Docker Deployment

Build the Docker image:

docker build -t wbi .

Run the Docker container:

docker run -p 5000:5000 wbi

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