GovGIS Nov2023 Slim Spatial
Provides a Dockerized framework combining PostGIS and pgvector to process and serve comprehensive geospatial data with vector similarity search capabilities.
Acerca de
This Dockerized project delivers a robust framework for managing and querying extensive geospatial datasets. It integrates PostGIS for advanced spatial data storage and manipulation, along with pgvector for efficient high-dimensional vector similarity searches within PostgreSQL. The setup includes an initializer for the `govgis_nov2023` dataset and pgAdmin for streamlined database management, offering a comprehensive solution for geospatial data processing and serving. It also features an MCP server powered by `fastmcp` for further integration and automation.
Características Principales
- Dockerized PostGIS and pgvector integration
- High-dimensional vector similarity search
- Geospatial data storage and manipulation
- Automated database initialization with `govgis_nov2023` dataset
- Web-based database management via pgAdmin
- 2 GitHub stars
Casos de Uso
- Setting up a local development environment for `govgis_nov2023` dataset exploration
- Implementing vector similarity search on geospatial metadata
- Developing applications requiring geospatial data storage and advanced querying
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