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---
title: govgis_nov2023-slim-faiss
emoji: 🌎
colorFrom: green
colorTo: blue
sdk: streamlit
sdk_version: 1.29.0
app_file: app.py
pinned: true
license: mit
---
# govgis_nov2023-slim-faiss
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# govgis_nov2023-slim-faiss
πŸ€– This README was written by GPT-4. πŸ€–
## Features
- **Semantic Search on GIS Metadata**: Leverages the `govgis_nov2023` dataset to provide detailed insights into numerous GIS servers and layers.
- **Natural Language Query Processing**: Uses Claude-Instant and Claude-2.1 models to interpret and rephrase user queries (optional).
- **Advanced Document Retrieval**: Integrates FAISS vector store for efficient and relevant document retrieval based on query semantics.
- **Customizable User Experience**: Sidebar controls to adjust search parameters and input fields for queries.
## Dataset Overview
- **Content**: The app is built around the `govgis_nov2023` dataset, which documents metadata from 1684 government ArcGIS servers, detailing almost a million individual layers.
- **Unique Snapshot**: Provides a unique snapshot of these servers, with metadata including field information for feature layers and cell size for raster layers.
## User Interface Guide
- Adjust search settings like result limits and response generation parameters in the sidebar.
- Securely enter your Anthropic API key for model access.
- Submit natural language queries related to GIS data.
## Contributions
We welcome contributions. Please follow the standard fork and pull request process.
## Support and Contact
For support, please raise an issue on GitHub or in the HuggingFace space.
## License
This project is under the [MIT License](LICENSE.md).
## Acknowledgments
Thanks to the Huggingface and Streamlit communities, and special acknowledgment to Joseph Elfelt and the creators of the `restgdf` library for their contributions to the GIS field.
## TODO
- [ ] Add an open source model like `HuggingFaceH4/zephyr-7b-beta`
- [ ] Hybrid search w/ bm25 or similar
- [ ] Find a lightweight way to incorporate geospatial filtering
- [ ] Add more parameters