TroglodyteDerivations/World_Explorer_with_DeepSeek_AI

Model Card: World Explorer with DeepSeek AI

Model Details

Model Name: World Explorer with DeepSeek AI
Model Type: Geographic Information System with AI Integration
Architecture: Dash Web Application with Folium Maps and DeepSeek Language Model
Integration: mlx-community/DeepSeek-V3.1-4bit, Dash, Folium
Version: 1.0.0
Release Date: September 5, 2025
Developers: Martin Rivera

Model Description

The World Explorer with DeepSeek AI is an interactive web application that combines geographic visualization with advanced language model capabilities. It integrates:

• mlx-community/DeepSeek-V3.1-4bit: A quantized version of the DeepSeek V3.1 language model optimized for MLX
• Dash: A Python framework for building analytical web applications
• Folium: A Python library for creating interactive maps and geographic visualizations

This application provides an immersive experience for exploring world geography, country information, capitals, and famous landmarks through an intuitive interface powered by AI.

Intended Use

This model is designed for:

• Educational purposes for learning about world geography
• Tourism planning and destination research
• Geographic data visualization and exploration
• Demonstrating the integration of language models with geographic information systems
• Research in human-computer interaction with AI-powered geographic interfaces

Features

Core Capabilities

• Interactive world map with precise geographic coordinates
• Country information including capitals and coordinates
• Detailed landmark data with exact geographic positions
• AI-powered natural language queries about geographic information
• Real-time responses to questions about countries, capitals, and landmarks

Technical Integration

• MLX-optimized DeepSeek model for efficient inference
• Responsive Dash web interface with Bootstrap styling
• Folium-based interactive maps with marker clusters
• Multi-threaded model loading for non-blocking user experience
• Advanced query parsing for geographic context understanding

Data

The application uses a comprehensive dataset of 10 countries with:

• Precise coordinates for each country's capital
• 30 famous landmarks with exact geographic coordinates
• Curated information about each geographic feature

Countries Included:

• France, United States, Japan, India, Brazil
• Egypt, Australia, Italy, China, United Kingdom

Landmark Examples:

• Eiffel Tower (48.858222, 2.2945)
• Great Wall of China (40.68, 117.23)
• Taj Mahal (27.175, 78.041944)
• Statue of Liberty (40.689167, -74.044444)
• Pyramids of Giza (29.9725, 31.128333)

Installation and Usage

Requirements

dash==2.14.2
dash-bootstrap-components==1.5.0
folium==0.15.1
pandas==2.1.4
numpy==1.26.4
mlx==0.0.6
transformers==4.37.2

Installation

git clone <repository>
cd world-explorer-deepseek
pip install -r requirements.txt

Running the Application

python app.py

The application will be available at http://localhost:8050

Model Setup

The application requires the MLX-optimized DeepSeek model from:

MODEL_PATH = "/Users/martinrivera/deepseek_v3_1_4bit_mlx/deepseek_v3_4bit" (Modify with your own MODEL_PATH = "path/to DeepSeek")

Performance

Response Quality

The model provides accurate geographic information with:

• Precise coordinate data for all locations
• Context-aware responses based on user queries
• Natural language understanding of geographic concepts
• Multi-level information retrieval (country → capital → landmarks)

Efficiency

• 4-bit quantization for reduced memory footprint
• MLX optimization for Apple Silicon performance
• Async model loading for responsive user experience
• Efficient geographic data structures for quick retrieval

Limitations

Current Limitations

• Dataset limited to 10 countries and 30 landmarks
• Requires specific model path configuration
• Optimized for macOS with Apple Silicon
• English language queries only

Geographic Coverage

While the application includes major countries and landmarks, it does not represent a complete global dataset. Users should note that:

• Some countries and regions are not included
• Landmark selection focuses on well-known tourist destinations
• Coordinate precision varies based on source data

Ethical Considerations

Data Accuracy

All geographic data has been verified from multiple sources, but users should:

• Verify critical information from official sources
• Understand that coordinates may have slight variations between sources
• Recognize that some landmarks span large areas (e.g., Great Barrier Reef)

Privacy

• The application does not collect user data
• All processing happens locally when possible
• No personal information is stored or transmitted

Future Improvements

Planned enhancements include:

• Expanded geographic coverage to more countries
• Additional landmark categories (natural wonders, historical sites)
• Multi-language support
• User-contributed data features
• Advanced visualization options (3D maps, time-based data)
• Integration with real-time geographic data sources

Citation

If you use this model in your research or projects, please cite:

@software{world_explorer_deepseek_2025,
  title = {World Explorer with DeepSeek AI},
  author = {Rivera, Martin},
  year = {2025},
  url = {https://huggingface.co/mlx-community/DeepSeek-V3.1-4bit},
  note = {Integration of MLX-optimized DeepSeek with Dash and Folium}
}

License

This project integrates multiple components with different licenses:

• DeepSeek Model: Subject to DeepSeek's model license terms
• Dash: MIT License
• Folium: MIT License
• Application Code: MIT License

Users should review and comply with all respective license terms.

Contact

For questions about the DeepSeek model:

• Hugging Face: mlx-community/DeepSeek-V3.1-4bit

Acknowledgements

This project builds upon:

• DeepSeek AI for the language model capabilities
• MLX community for Apple Silicon optimization
• Plotly for the Dash framework
• Python Folium library for geographic visualization
• OpenStreetMap for base map data

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This model card was generated as part of the World Explorer with DeepSeek AI project to provide transparency about the capabilities, limitations, and appropriate use of this geographic AI application.