Upload README.md with huggingface_hub

README.md

@@ -1,47 +1,192 @@
----
-language:
-- en
-license:
-- mit
-task_categories:
-- text-classification
-- document-question-answering
-tags:
-- warp-drive
-- physics
-- quantum-mechanics
-- spacetime
----
-
-# Warp Drive Research Dataset
-
-This dataset contains research papers, technical documents, and scientific analyses related to warp drive technology and related physics concepts. The data is organized into several key categories including quantum physics, spacetime mechanics, propulsion theory, and more.
-
-## Dataset Structure
-
-The dataset is organized into the following main categories:
-- Quantum Physics
-- Spacetime
-- Experimental Physics
-- Propulsion Theory
-- Materials Science
-- Energy Systems
-- Theoretical Physics
-- Computational Physics
-
-Each category contains relevant research papers, experimental data, and technical documentation.
-
-## Last Updated
-2024-12-21
-
-## Citation
-If you use this dataset, please cite it as:
-```
-@dataset{warpdrive2024,
-  author       = {GotThatData},
-  title        = {Warp Drive Research Dataset},
-  year         = {2024},
-  publisher    = {Hugging Face},
-  howpublished = {https://huggingface.co/datasets/GotThatData/warp-speed}
-}
-```
+# WarpSpeed: Advanced Star Trek Technology Analysis Engine
+
+An advanced AI system for processing, analyzing, and simulating Star Trek technology concepts using quantum computing principles and advanced reasoning engines.
+
+## 🌟 Overview
+
+WarpSpeed is a cutting-edge AI research platform that combines quantum computing principles with advanced machine learning to analyze and simulate theoretical Star Trek technologies. Our goal is to bridge science fiction and real-world physics through rigorous computational analysis.
+
+## 🚀 Features
+
+- **Quantum-Enhanced Processing**
+  - Quantum computing simulation integration
+  - Advanced tensor network processing
+  - Quantum-inspired optimization algorithms
+  - Distributed quantum knowledge graphs
+
+- **Advanced AI Reasoning Engines**
+  - Multi-modal semantic understanding
+  - Causal and abductive reasoning
+  - Meta-cognitive processing layers
+  - Explainable AI with physics validation
+
+- **Real-time Analysis & Monitoring**
+  - System performance analytics
+  - Resource utilization tracking
+  - Quantum state monitoring
+  - Simulation health metrics
+
+- **Scientific Data Processing**
+  - Multi-source data integration
+  - Advanced preprocessing pipelines
+  - Physics-based validation
+  - Quality assurance protocols
+
+## 🛠️ Installation
+
+1. Clone the repository:
+```bash
+git clone https://github.com/Saifullah62/warpSpeed.git
+cd warpSpeed
+```
+
+2. Set up the environment:
+```bash
+make setup-env
+make dev-install
+```
+
+3. Configure settings:
+```bash
+cp .env.example .env
+# Edit .env with your configurations
+```
+
+4. Start the development server:
+```bash
+make run-dev
+```
+
+## 📚 Documentation
+
+- [Complete Documentation](docs/index.rst)
+- [Development Guide](docs/development/automation.rst)
+- [API Reference](docs/api/index.rst)
+- [Monitoring Guide](docs/monitoring/index.rst)
+
+## 🧪 Testing
+
+Run the test suite:
+```bash
+make test
+```
+
+Run specific tests:
+```bash
+make test PYTEST_ARGS="tests/unit/"
+```
+
+## 🔧 Development
+
+1. Create a feature branch:
+```bash
+git checkout -b feature/your-feature
+```
+
+2. Make changes and test:
+```bash
+make lint test docs
+```
+
+3. Submit a pull request
+
+## 📊 Monitoring
+
+Access monitoring dashboards:
+- System Health: http://localhost:8000/dashboard
+- Performance Metrics: http://localhost:8000/metrics
+- Resource Usage: http://localhost:8000/resources
+
+## 🤝 Contributing
+
+1. Read our [Contributing Guide](.github/CONTRIBUTING.md)
+2. Fork the repository
+3. Create your feature branch
+4. Submit a pull request
+
+## 📝 License
+
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
+
+## 🔗 Links
+
+- [Project Documentation](https://docs.warpspeed.ai)
+- [API Documentation](https://api.warpspeed.ai)
+- [Issue Tracker](https://github.com/Saifullah62/warpSpeed/issues)
+
+## 🏗️ Project Structure
+
+```
+warpSpeed/
+├── config/           # Configuration files
+├── docs/            # Documentation
+├── src/             # Source code
+│   ├── monitoring/  # Monitoring system
+│   ├── knowledge/   # Knowledge processing
+│   └── data/        # Data management
+├── tests/           # Test suites
+├── scripts/         # Utility scripts
+└── tools/           # Development tools
+```
+
+## ✨ Acknowledgments
+
+- Star Trek and related marks are trademarks of CBS Studios Inc.
+- This project is for educational and research purposes only.
+
+## Dataset
+
+### Location and Access
+The Star Trek Technology dataset is hosted on Hugging Face's dataset repository for easy access and version control. You can find it at:
+- 🤗 Dataset: [Star Trek Technology Dataset](https://huggingface.co/datasets/Saifullah/StarTrekTechnology)
+
+### Dataset Contents
+The dataset includes:
+- Research papers metadata
+- Processed technical descriptions
+- Knowledge graph relationships
+- Technology classifications
+- Temporal markers and references
+
+### Using the Dataset
+
+1. **Direct Download**
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Saifullah/StarTrekTechnology")
+```
+
+2. **Manual Download**
+   - Visit the [dataset page](https://huggingface.co/datasets/Saifullah/StarTrekTechnology)
+   - Click on "Files and versions"
+   - Download the required files
+
+3. **Local Setup**
+   - Create a `data` directory in your project root
+   - Extract the downloaded files into this directory
+   - The application will automatically detect and use the local data
+
+### Dataset Structure
+```
+data/
+├── papers_metadata.json       # Research papers metadata
+├── processed_data/           # Processed and cleaned data
+└── knowledge_graph/         # Graph relationships and connections
+```
+
+### Version Information
+- Current Version: 1.0.0
+- Last Updated: December 24, 2024
+- License: MIT
+
+### Citation
+If you use this dataset in your research, please cite:
+```bibtex
+@dataset{startrek_tech_2024,
+  author = {Saifullah},
+  title = {Star Trek Technology Dataset},
+  year = {2024},
+  publisher = {Hugging Face},
+  url = {https://huggingface.co/datasets/Saifullah/StarTrekTechnology}
+}