The Energy Language Model (ELM) software provides interfaces to apply Large Language Models (LLMs) like ChatGPT and GPT-4 to energy research. For example, you might be interested in:
Chunking text documents and embedding into a vector database
Building an automated data extraction workflow using decision trees
Building a chatbot app that interfaces with reports from OSTI
Installing ELM
NOTE: If you are installing ELM to run ordinance scraping and extraction, see the ordinance-specific installation instructions.
Option #1 (basic usage):
pip install NREL-elm
Option #2 (developer install):
from home dir, git clone git@github.com:NREL/elm.git
- Create elm environment and install package
Create a conda env: conda create -n elm
Run the command: conda activate elm
cd into the repo cloned in 1.
Prior to running pip below, make sure the branch is correct (install from main!)
Install elm and its dependencies by running: pip install . (or pip install -e . if running a dev branch or working on the source code)
Acknowledgments
This work was authored by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the DOE Wind Energy Technologies Office (WETO), the DOE Solar Energy Technologies Office (SETO), and internal research funds at the National Renewable Energy Laboratory. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.
1 maintainer
Metadata
1 maintainer
Release files for nrel-elm 0.0.34
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| nrel_elm-0.0.34.tar.gz | 119.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| nrel_elm-0.0.34-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 261.9 kB
Release files / nrel_elm-0.0.34.tar.gz
| Download URL | nrel_elm-0.0.34.tar.gz |
|---|---|
| Size | 119.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
39b9cea124a66915eb9a47d13e931b5b2d8352bf3100a10d630f958adebaf02e
|
|
BLAKE2b-256 checksum How to use checksums |
76fc8c9910d1629d7397c6593e88c36da8169c29e87e138111c2983ec65b3360
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 1, 2025.
Transparency logRelease files / nrel_elm-0.0.34-py3-none-any.whl
| Download URL | nrel_elm-0.0.34-py3-none-any.whl |
|---|---|
| Size | 142.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
6ed8ed1f3edfbc6fe3e77e9fe05114271d9d28d22476c96041bdc727ec7c6337
|
|
BLAKE2b-256 checksum How to use checksums |
b50e0898bc80431eb17e7d0744321fab1ba1e39fae0ba2c9e8634c042feb31f5
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 1, 2025.
Transparency log
