README.md

---
language: code
tags:
- ai
- chatbot
- neural-network
- post-quantum
- conversational-ai
- knowledge-base
- philosophy
- education
- governance
- literature
- mathematics
- computer-science
- physics
- mathematics
- psychology
- emotion-handling
- intent-classification
- response-generation
- quantum-inspired
- lightweight
- offline-capable
- multilingual
license: mit
datasets:
- custom
---

# Xe - Post-Quantum AI

A lightweight conversational AI framework combining quantum-inspired neural networks with domain knowledge and post-quantum cryptography utilities.

## Model Description

Xe is a hybrid AI system featuring:
- **Quantum-inspired Neural Network**: A feedforward neural network with attention-like mechanisms
- **Conversational Brain**: Intent classification and learned response generation
- **Knowledge Base**: Comprehensive domain knowledge in philosophy, education, governance, literature, mathematics, computer science, and physics
- **Emotional Intelligence**: Empathy-based response adaptation
- **Post-Quantum Cryptography**: Utilities for quantum-resistant security

## Model Architecture

- **Type**: Quantum-inspired feedforward neural network
- **Input Size**: 64 features (bag-of-words representation)
- **Hidden Layers**: 2 layers with 32 and 11 neurons respectively
- **Activation**: ReLU for hidden layers, linear for output
- **Learning Rate**: 0.01 (optimized)
- **Loss Function**: Mean Squared Error

## Training Data

The model was trained on:
- 80 conversation samples (expanded training)
- Comprehensive knowledge base across 17 domains
- Philosophical, scientific, mathematical, and cultural knowledge
- Last training: 2026-07-22

## Knowledge Domains

The model is expert in:
- **Humanities**: Philosophy, literature, history, art
- **Sciences**: Physics, biology, chemistry, astronomy
- **Mathematics**: Calculus, algebra, statistics, logic
- **Social Sciences**: Psychology, law, economics, governance
- **Technology**: Computer science, AI, current science
- **Business**: Marketing, engineering, medicine

## Intended Use

- **Primary**: Conversational AI and chatbot applications
- **Secondary**: Knowledge retrieval and educational assistance
- **Domains**: Philosophy, education, governance, literature, mathematics, computer science, physics

## Limitations

- The model is designed for conversational purposes and may not handle all edge cases
- Knowledge is based on training data up to July 2026
- Not suitable for critical decision-making without human oversight

Last updated: July 21, 2026

## Usage

```python
from huggingface_hub import hf_hub_download
import json
import numpy as np

# Download model files
model_path = hf_hub_download(repo_id="Travellers/xe", filename="xe_model.json")
brain_path = hf_hub_download(repo_id="Travellers/xe", filename="xe_brain.json")

# Load model
with open(model_path) as f:
    model_config = json.load(f)

# Load brain data
with open(brain_path) as f:
    brain_data = json.load(f)
```

## Installation

```bash
pip install xe
```

## CLI Usage

```bash
xe chat          # Start interactive chat
xe train         # Train the model
xe optimize      # Run quantum-inspired optimization
xe keygen        # Generate post-quantum keypair
```

## Example Conversation

```
User: Hello
Bot: Hi there! I'm Xe, your post-quantum AI buddy.

User: How are you?
Bot: Oh, I'm wonderful, actually! Every chat teaches me something.

User: What is the derivative?
Bot: The derivative measures instantaneous rate of change: f'(x) = lim[h->0] (f(x+h)-f(x))/h.
```

## Files

- `xe_model.json`: Neural network weights and architecture
- `xe_brain.json`: Conversation history, learned responses, and knowledge
- `README.md`: This documentation

## License

MIT License - See LICENSE file for details.

## Author

Created by the Xe AI project. A post-quantum conversational AI framework.