natural-language-geocoding 0.1.3

Natural Language Geocoding implements an AI technique to convert natural language descriptions of spatial areas into polygons.

natural-language-geocoding

Natural Language Geocoding can geocode natural language descriptions of places on the Earth into the geometry.

Try it out: element84.com/natural-language-geocoding/

Installing and Using

pip install natural-language-geocoding
natural-language-geocoding init

See documentation on how to configure and populate the OpenSearch cluster in Sources.

Running the demo

There's a streamlit demo in src/natural_language_geocoding_demo. It can be run by following these steps.

1. Set up AWS credentials. The demo uses AWS Bedrock Anthropic Claude as the LLM. Valid AWS access keys to an account need to be present.
2. Follow steps for local development
3. Create and populate an OpenSearch cluster following the instructions in Sources.
4. Run scripts/run_demo.sh
5. It will open in your browser

Developing

1. Install python and uv
2. Checkout the code
3. Run scripts/recreate_venv.sh
4. Run PYTHONPATH=src python src/natural_language_geocoding/main.py init
5. Run pre-commit install to install the pre commit checks
6. Make changes
7. Verify linting passes scripts/lint.sh
8. Commit and push your changes

Contributions

We are happy to take contributions! It is best to get in touch with the maintainers about larger features or design changes before starting the work, as it will make the process of accepting changes smoother.

Contributor License Agreement (CLA)

Everyone who contributes code to natural language geocoding will be asked to sign a CLA, which is based off of the Apache CLA.

• Download a copy of one of the following from the docs/cla directory in this repository:

  • Individual Contributor (You're using your time): 2024_1_24-Natural-Language-Geocoding-Open-Source-Contributor-Agreement-Individual.pdf
  • Corporate Contributor (You're using company time): 2024_1_24-Natural-Language-Geocoding-Open-Source-Contributor-Agreement-Corporate.pdf

• Sign the CLA -- either physically on a printout or digitally using appropriate PDF software.

• Send the signed CLAs to Element 84 via one of the following methods:

  • Emailing the document to [e-mail]
  • Mailing a hardcopy to: Element 84, 210 N. Lee Street Suite 203 Alexandria, VA 22314, USA.

Attribution

See Sources for attribution and licensing information.