DEPRECATED: This repository is still useful for context and to see an initial implementation of this idea. However, this work is being continued in https://github.com/developmentseed/haystac with a more "proper" structure using LangChain
This is inspired by Simon Willison's blog-post: https://til.simonwillison.net/llms/python-react-pattern
The idea here is to develop a natural language interface to a STAC API endpoint, currently the Microsoft Planetary Computer STAC Catalog.
The code is currently very rudimentary and experimental, but already shows promising results.
Create an environment variable called OPENAI_API_KEY with your OpenAI API key.
python
from main import query
> query("Can you get me satellite imagery for Seattle for 10th December, 2018?")
Observation: The STAC query returns a list of assets that are available for the given parameters of the bounding box and datetime, which includes imagery from NOAA GOES satellite (GLM-L2-LCFA/2018/345/00) as well as MODIS collection 6.1 (MYD21A2.A2018345.h09v04.061.2021350231530) which has several different assets available, including metadata and various thermal bands. The rendered preview image can be viewed at https://planetarycomputer.microsoft.com/api/data/v1/item/preview.png?collection=modis-21A2-061&item=MYD21A2.A2018345.h09v04.061.2021350231530&assets=LST_Day_1KM&tile_format=png&colormap_name=jet&rescale=255%2C310&format=png
In the above example, ChatGPT constructs queries to Wikipedia, gets the bounding box for Seattle, and uses that to construct a query to the STAC API for the bounding box and datetime requests. It currently only processes the first two results returned, but this can be easily improved.
This is a very rough quick and dirty PoC. To improve this:
- Move from wikipedia to using a real geocoder to fetch bounding boxes for a place
- Allow it to use more complex STAC search functionality
- Format the STAC search result object more appropriately to send back to ChatGPT for it to interpret results.
- Augment ChatGPT's natural language answer with all the links, etc. from the actual STAC API response.
This is now wrapped in a lightweight FastAPI application
docker build -t fastapi-chatgpt-app .docker run -p 8000:8000 -e OPENAI_API_KEY=<your_openai_api_key> fastapi-chatgpt-app- Send a request like this:
http://localhost:8000/chatgpt?prompt=%22find%20me%20satellite%20imagery%20in%20Bangalore%20for%20December%2014,%202017%22