A prototype language model interface for generating geological models!
Leveraging the power of Llama 4 and GemPy, geo-lm is a Python package designed for generative geology. It utilizes the latest advancements in large language models to understand geological information and translate it into 3D geological models.
geo-lm employs Llama 4's multi-modal inference capabilities to automate the process of creating geological models from existing documentation. The workflow involves the following key steps:
- Document Understanding: The package can process geology reports and documents by reading OCRed text and interpreting extracted maps.
- Geological Knowledge Consolidation: The interpreted information for a specific locality is then consolidated into a structured "geology DSL" (Domain Specific Language). This DSL encodes crucial geological knowledge, including:
- Lithology data (rock types and their properties)
- Structural interpretations (faults, folds, unconformities)
- Cross-cutting relations between geological units
- Relative and absolute time-ordering of geological events.
- 3D Model Generation: Finally, the geology DSL is parsed and used as input for GemPy, an open-source Python library for implicit geological modeling and 3D visualization. This allows for the automatic generation of 3D representations of subsurface geology.
geo-lm is a Python package managed with Poetry. To set up your environment, ensure you have Poetry installed. If not, you can install it following the instructions on the official Poetry website.
Once Poetry is installed, navigate to the directory containing the pyproject.toml file and run:
poetry installThis command will create a virtual environment and install all the necessary dependencies, including GemPy.
Before running the example script, you'll need to set your Llama 4 API key as an environment variable:
export LLAMA_API_KEY=<your-key-here>Replace <your-key-here> with your actual Llama 4 API key.
The provided example script run.py demonstrates how to initiate the geological modeling process using Llama 4. To run it, use the following command:
python run.py \
--input-mode llm \
--prompt-type default \
--llm-output-dir input-data/llm-generatedThis command will instruct the script to use the language model (--input-mode llm) with a default prompting strategy (--prompt-type default) and save the LLM's output (the generated geology DSL) to the input-data/llm-generated directory.
This repo was originally tested on the following (open access?) paper:
Patrick B. Redmond, Marco T. Einaudi; The Bingham Canyon Porphyry Cu-Mo-Au Deposit. I. Sequence of Intrusions, Vein Formation, and Sulfide Deposition. Economic Geology 2010;; 105 (1): 43–68. doi: https://doi.org/10.2113/gsecongeo.105.1.43
We welcome contributions to geo-lm! If you have ideas for improvements, new features, or bug fixes, please feel free to open an issue or submit a pull request.
This package was originally called hutton-lm, but was renamed to geo-lm last minute!
