README.md

metadata

title: Geoai Coding Agent
emoji: 🌍
colorFrom: pink
colorTo: red
sdk: gradio
sdk_version: 6.3.0
app_file: app.py
pinned: false
license: agpl-3.0
tags:
  - geospatial
  - geospatial-ai
  - AI
  - ML
  - DL
  - LLM
  - satellite-data
  - earth-observation
  - nlp
  - maps
  - data-visualization
  - natural-language
  - gradio
  - huggingface
short_description: GeoAI Coding Agent - Geospatial AI Coding Assistant"

🌍 GeoAI Coding Agent

A Geospatial AI Coding Assistant powered by multiple LLMs via HuggingFace Inference Providers.

Specialized in GDAL/OGR, Rasterio, GeoPandas, xarray, and geospatial development across multiple programming languages. Designed for beginner and intermediate learners with educational explanations.

✨ Features

• 🤖 Multiple AI Models: Choose from 6 different models (DeepSeek, Kimi, Llama, MiniMax, GLM, Mistral)
• 🗺️ Geospatial Expertise: Deep knowledge of GDAL, Rasterio, GeoPandas, PyProj, xarray, and rioxarray
• 📚 Educational Focus: Responses include code explanations, step-by-step logic, and tips for beginners
• 💻 Multi-Language Support: Python, Java, C/C++, JavaScript, TypeScript, Rust
• 📥 Download Options: Export responses as Markdown or code files
• 🎨 Code Editor Style UI: Syntax highlighting with dark theme
• ⚡ Streaming Responses: Real-time token streaming for better UX

🤖 Available Models

Model	Provider	Speed	Best For
DeepSeek V3.2	Novita	Medium	Complex geospatial tasks, detailed explanations
Kimi K2 Instruct	Novita	Medium	General coding, good balance
Llama 3.1 8B	Novita	Fast	Quick answers, simple tasks
MiniMax M2.1	Novita	Medium	Creative solutions
GLM 4.7 Flash	Novita	Fast	Fast responses, basic tasks
Mistral 7B v0.2	Featherless	Fast	Quick prototyping

💡 Tip: Larger models provide better results but take longer. Smaller models are faster for simple queries.

🚀 Quick Start

Local Development

1. Clone the repository

   git clone https://github.com/rifatSDAS/geoai-coding-agent.git
   cd geoai-coding-agent
   

2. Create virtual environment

   python -m venv venv
   source venv/bin/activate  # Linux/Mac
   # or
   venv\Scripts\activate  # Windows
   

3. Install dependencies

   pip install -r requirements.txt
   

4. Run the application

   python app.py
   

5. Open in browser: Navigate to http://localhost:7860

6. Enter your HuggingFace token: Get one at huggingface.co/settings/tokens

Run Tests

pytest test_app.py -v

🐳 HuggingFace Spaces Deployment

1. Create a new Space at huggingface.co/new-space

   • Select Gradio as the SDK
   • Choose CPU basic (free tier)

2. Upload files

   • app.py
   • config.py
   • requirements.txt
   • README.md (optional)

3. That's it! The Space will automatically build and deploy.

📁 Project Structure

geoai-coding-agent/
├── app.py              # Main Gradio application
├── config.py           # Configuration, prompts, templates
├── test_app.py         # Unit tests
├── requirements.txt    # Python dependencies
├── .gitignore          # Git ignore rules
└── README.md           # This file

🎯 Example Queries

• "Read a GeoTIFF with rasterio and calculate NDVI from Sentinel-2 bands"
• "Convert shapefile to GeoJSON using GDAL/OGR in Python"
• "Reproject a raster from EPSG:4326 to EPSG:32632 using rasterio"
• "Clip a large COG raster to a polygon boundary using rioxarray"
• "Create a spatial join between two GeoDataFrames in GeoPandas"
• "Implement parallel raster processing with GDAL in C++"

⚙️ Configuration

Key settings in config.py:

Parameter	Default	Description
DEFAULT_MODEL	DeepSeek V3.2	Default model selection
MAX_NEW_TOKENS	2048	Maximum response length
TEMPERATURE	0.3	Sampling temperature (lower = more focused)
TOP_P	0.9	Nucleus sampling threshold
AVAILABLE_MODELS	(see table above)	Dictionary of available models & providers

🔑 API Token

This application requires a HuggingFace API token with Inference Provider permissions.

Required permissions:

• ✅ Make calls to Inference Providers

Get your free token at: huggingface.co/settings/tokens

For HuggingFace Spaces deployment, add the token as a Secret named HF_TOKEN in Space Settings.

🛠️ Supported Languages

Language	Extension	Use Case
Python	.py	GDAL, Rasterio, GeoPandas
Java	.java	GeoTools, JTS
C/C++	.c, .cpp	GDAL C API, performance
JavaScript	.js	Leaflet, OpenLayers, Turf.js
TypeScript	.ts	Type-safe geospatial apps
Rust	.rs	GDAL Rust bindings, geo crate

📦 Dependencies

• gradio: Web UI framework
• huggingface-hub: HF Inference API client
• pytest: Testing framework

🙏 Acknowledgments

• Inspired by GeoAI-Assistance-Ext VS Code Extension
• Powered by multiple LLMs via HuggingFace Inference Providers
• Built with Gradio

About the Developer

Built by Dr. Kazi Rifat Ahmed, a Full Stack Geospatial AI Engineer, Co-founder and Technical Lead for Satellite Data Services business in Space sector.

Contributing

Contributions welcome! Please feel free to submit issues and pull requests.

Contact

For collaboration opportunities in satellite data services & applications, large-scale satellite data analytics, geospatial AI, blockchain & quantum computing for geospatial applications, or advanced geospatial science, technology & applications, feel free to reach out!

Portfolio at https://rifatsdas.github.io/

📄 License

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0).

See LICENSE for details.

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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference