--- title: Gazet emoji: "\U0001F5FA" colorFrom: green colorTo: blue sdk: docker app_port: 7860 --- # Gazet Gazet logo Lean natural-language geocoder with GIS operations over Overture and Natural Earth parquet datasets. Gazet is built to be easily packagable and minimal in setup, trying to push the boundaries on how small we can go in setup for LLM driven data applications. It is built for working with small language models and parquet files. The name inspired by [Gazetteer](https://en.wikipedia.org/wiki/Gazetteer). A gazetteer is a geographical dictionary or directory used in conjunction with a map or atlas. [![Model on HF](https://huggingface.co/datasets/huggingface/badges/resolve/main/model-on-hf-sm.svg)](https://huggingface.co/developmentseed/gazet-model) [![Dataset on HF](https://huggingface.co/datasets/huggingface/badges/resolve/main/dataset-on-hf-sm.svg)](https://huggingface.co/datasets/developmentseed/gazet-dataset) ## Local setup ### Python setup Install python dependencies using [uv](https://docs.astral.sh/uv/) ```bash uv sync --extra dev --extra demo ``` ### Data preparation 1. Download Overture divisions data 2. Download the 10m physical layer from [Natural Earth](https://www.naturalearthdata.com/downloads/10m-physical-vectors/) 3. Unzip the data 4. Convert natural earth data to parquet Example for downloading overture ```bash aws s3 sync s3://overturemaps-us-west-2/release/2026-02-18.0/theme=divisions/type=division_area/ data/overture/divisions_area ``` Example for running conversion script for natural earth ```bash unzip ~/Downloads/10m_physical.zip -d data/natural_earth python -m ingest.convert_natural_earth data/natural_earth ``` ### Based on ollama For now, gazet relies on [ollama](https://ollama.com/). For remote (cloud) models, ensure you are loged into Ollama. ## Usage ```bash python -m gazet # then GET http://localhost:8000/search?q=Border%20between%20Loja%20and%20Piura ``` ### API + Streamlit demo ```bash uv run uvicorn gazet.api:app --reload # API on :8000 uv run streamlit run gazet_demo.py # demo UI ``` ## Modules | Module | Contents | | --- | --- | | `config.py` | data paths, model name, SQL schema description | | `schemas.py` | `SUBTYPES`, `COUNTRIES`, `Place`, `PlacesResult` | | `lm.py` | DSPy signatures + LM init (`extract`, `write_sql`) | | `search.py` | fuzzy search against `divisions_area` / `natural_earth` | | `sql.py` | code-act SQL generation loop | | `export.py` | GeoJSON FeatureCollection writer | | `api.py` | FastAPI app with `/search?q=...` returning GeoJSON FeatureCollection | ## Design notes - `api.py` exposes GET `/search?q=`; returns GeoJSON FeatureCollection and logs intermediate output. - LM is initialised at import time in `lm.py`, suitable for a long-lived server process. - Data lives in `data/overture/` and `data/natural_earth_geoparquet/` (not tracked in git). ## Attributions Logo icon: search globe by popcornarts from Noun Project (CC BY 3.0)