MLIP plugins for ORCA ExtTool (UMA, ORB, MACE, AIMNet2)
Project description
orca-mlips
MLIP (Machine Learning Interatomic Potential) plugins for ORCA ExtTool (ProgExt) interface.
Four model families are currently supported:
- UMA (fairchem) — default model:
uma-s-1p1 - ORB (orb-models) — default model:
orb_v3_conservative_omol - MACE (mace) — default model:
MACE-OMOL-0 - AIMNet2 (aimnetcentral) — default model:
aimnet2
All backends provide energy and gradient, and can output an analytical Hessian in ORCA .hess format via --dump-hessian.
An optional implicit-solvent correction (xTB) is also available via --solvent.
The model server starts automatically and stays resident in memory, so repeated calls during optimization are fast.
Requires Python 3.9 or later.
If you use Gaussian 16, see also: https://github.com/t-0hmura/g16-mlips
Quick Start (Default = UMA)
- Install PyTorch suitable for your CUDA environment.
pip install torch==2.8.0 --index-url https://download.pytorch.org/whl/cu129
- Install the package with the UMA profile. If you need ORB/MACE/AIMNet2, use
orca-mlips[orb]/orca-mlips[mace]/orca-mlips[aimnet2].
pip install "orca-mlips[uma]"
- Log in to Hugging Face for UMA model access. (Not required for ORB/MACE/AIMNet2)
huggingface-cli login
UMA model is on Hugging Face Hub. You need to log in once (See https://github.com/facebookresearch/fairchem):
- Use in an ORCA input file. If you use ORB/MACE/AIMNet2, use
ProgExt "orb"/ProgExt "mace"/ProgExt "aimnet2". For detailed ORCA External Tool /ExtOptusage, see https://www.faccts.de/docs/orca/6.1/tutorials/workflows/extopt.html
! ExtOpt Opt
%pal
nprocs 8
end
%method
ProgExt "uma"
end
* xyz 0 1
O 0.000000 0.000000 0.000000
H 0.758602 0.000000 0.504284
H -0.758602 0.000000 0.504284
*
Other backends:
%method
ProgExt "orb"
end
%method
ProgExt "mace"
end
%method
ProgExt "aimnet2"
end
Implicit Solvent Correction (xTB)
You can use an implicit-solvent correction via xTB. To use it, install xTB and pass the --solvent option to Ext_Params.
Install xTB in your conda environment (or built from source):
conda install xtb
Use --solvent <name> through Ext_Params (examples: water, thf):
%method
ProgExt "uma"
Ext_Params "--solvent water"
end
%method
ProgExt "uma"
Ext_Params "--solvent thf"
end
For details, see SOLVENT_EFFECTS.md.
This implementation follows the solvent-correction approach described in: Zhang, C., Leforestier, B., Besnard, C., & Mazet, C. (2025). Pd-catalyzed regiodivergent arylation of cyclic allylboronates. Chemical Science, 16, 22656-22665. https://doi.org/10.1039/d5sc07577g
If citing this correction in a paper, you can use the following:
Implicit solvent effects were accounted for by integrating the ALPB [or CPCM-X] solvation model from the xtb package as an additional correction to UMA-generated energies, gradients, and Hessians.
Note:
--solvent-model cpcmx(CPCM-X) requires xTB built from source with-DWITH_CPCMX=ON. The conda-forgextbpackage does not include CPCM-X support. SeeSOLVENT_EFFECTS.mdfor build instructions.
Using Analytical Hessian (optional two-step workflow)
Optimization and TS searches can run without providing an initial Hessian — ORCA builds one internally. Providing an analytical Hessian from the MLIP via --dump-hessian + InHessName improves convergence, especially for TS searches.
Why two steps? ORCA has no API to receive Hessian data directly through
ExtTool. The only supported path is:
- dump Hessian with
--dump-hessian <file>in step 1,- read it in step 2 with
InHessName <file>.
Generate a .hess file first, then load it via InHessName.
TS Search
Step 1: Generate analytical Hessian via --dump-hessian
! ExtOpt Opt
%geom
MaxIter 1
end
%method
ProgExt "uma"
Ext_Params "--dump-hessian cla.hess"
end
* xyz 0 1
...
*
This runs a single-iteration optimization that triggers the ExtTool call and writes the analytical Hessian in ORCA .hess format. ! ExtOpt is required to make ORCA use the external tool instead of its own internal methods. The job may exit with a non-zero status (not converged), but the .hess file is created.
Step 2: TS optimization reading Hessian
! ExtOpt OptTS
%method
ProgExt "uma"
end
%geom
InHessName "cla.hess"
end
* xyz 0 1
...
*
ORCA reads the initial Hessian from the .hess file. The model server keeps the MLIP loaded so repeated calls during optimization are fast.
Geometry Optimization (with analytical Hessian)
Same two-step workflow with ! ExtOpt Opt instead of ! ExtOpt OptTS:
! ExtOpt Opt
%geom
MaxIter 1
end
%method
ProgExt "mace"
Ext_Params "--dump-hessian water.hess"
end
* xyz 0 1
...
*
then:
! ExtOpt Opt
%method
ProgExt "mace"
end
%geom
InHessName "water.hess"
end
* xyz 0 1
...
*
Installing Model Families
pip install "orca-mlips[uma]" # UMA (default)
pip install "orca-mlips[orb]" # ORB
pip install "orca-mlips[mace]" # MACE
pip install "orca-mlips[orb,mace]" # ORB + MACE
pip install "orca-mlips[aimnet2]" # AIMNet2
pip install "orca-mlips[orb,mace,aimnet2]" # ORB + MACE + AIMNet2
pip install orca-mlips # core only
Note: UMA and MACE have a dependency conflict (
e3nn). Use separate environments.
Local install:
git clone https://github.com/t-0hmura/orca-mlips.git
cd orca-mlips
pip install ".[uma]"
Model download notes:
- UMA: Hosted on Hugging Face Hub. Run
huggingface-cli loginonce. - ORB / MACE / AIMNet2: Downloaded automatically on first use.
Upstream Model Sources
- UMA / FAIR-Chem: https://github.com/facebookresearch/fairchem
- ORB / orb-models: https://github.com/orbital-materials/orb-models
- MACE: https://github.com/ACEsuit/mace
- AIMNet2: https://github.com/isayevlab/aimnetcentral
Advanced Options
See OPTIONS.md for backend-specific tuning parameters.
For solvent correction options, see SOLVENT_EFFECTS.md.
Command aliases:
- Short:
uma,orb,mace,aimnet2 - Prefixed:
orca-mlips-uma,orca-mlips-orb,orca-mlips-mace,orca-mlips-aimnet2
Troubleshooting
ProgExt "uma"runs the wrong plugin — UseProgExt "orca-mlips-uma"to avoid alias conflicts.ProgExt "aimnet2"runs the wrong plugin — UseProgExt "orca-mlips-aimnet2"to avoid alias conflicts.umacommand not found — Activate the conda environment where the package is installed.- UMA model download fails (401/403) — Run
huggingface-cli login. Some models require access approval on Hugging Face. - Works interactively but fails in PBS jobs — Use absolute path from
which umain the ORCA input.
Citation
If you use this package, please cite:
@software{ohmura2026orcamlips,
author = {Ohmura, Takuto},
title = {orca-mlips},
year = {2026},
month = {2},
version = {1.1.0},
url = {https://github.com/t-0hmura/orca-mlips},
license = {MIT},
doi = {10.5281/zenodo.18718009}
}
References
- ORCA ExtTool official tutorial (ExtOpt workflow): https://www.faccts.de/docs/orca/6.1/tutorials/workflows/extopt.html
- ORCA ExtTool: https://www.faccts.de/docs/orca/6.1/manual/contents/essentialelements/externaloptimizer.html
- ORCA external tools: https://github.com/faccts/orca-external-tools
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file orca_mlips-1.2.0.tar.gz.
File metadata
- Download URL: orca_mlips-1.2.0.tar.gz
- Upload date:
- Size: 39.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e9680b4a12faa23e48351df4cc4adcb582291524895dc741e8cec13efa772634
|
|
| MD5 |
4c4f254f71620e85ac0588b4e75b4cb9
|
|
| BLAKE2b-256 |
b9c843e8ea144019a90380319d3e25b816f3cc11c7ceaa2ddabc467534542548
|
Provenance
The following attestation bundles were made for orca_mlips-1.2.0.tar.gz:
Publisher:
release.yml on t-0hmura/orca-mlips
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
orca_mlips-1.2.0.tar.gz -
Subject digest:
e9680b4a12faa23e48351df4cc4adcb582291524895dc741e8cec13efa772634 - Sigstore transparency entry: 1123019442
- Sigstore integration time:
-
Permalink:
t-0hmura/orca-mlips@d86736b9f9998c667fd18ce01e16b51d2e97536f -
Branch / Tag:
refs/tags/v1.2.0 - Owner: https://github.com/t-0hmura
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
release.yml@d86736b9f9998c667fd18ce01e16b51d2e97536f -
Trigger Event:
release
-
Statement type:
File details
Details for the file orca_mlips-1.2.0-py3-none-any.whl.
File metadata
- Download URL: orca_mlips-1.2.0-py3-none-any.whl
- Upload date:
- Size: 35.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
61fcf60e16c9db505c22cb428a5868d14b2bb1a48b05d0188483e21fd0d8f05e
|
|
| MD5 |
912fa28505b4430933c4f865f535859a
|
|
| BLAKE2b-256 |
86901259ba49ec54a143f1413f75f9dc961fe6c94906af77d546c2e7940a58a4
|
Provenance
The following attestation bundles were made for orca_mlips-1.2.0-py3-none-any.whl:
Publisher:
release.yml on t-0hmura/orca-mlips
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
orca_mlips-1.2.0-py3-none-any.whl -
Subject digest:
61fcf60e16c9db505c22cb428a5868d14b2bb1a48b05d0188483e21fd0d8f05e - Sigstore transparency entry: 1123019443
- Sigstore integration time:
-
Permalink:
t-0hmura/orca-mlips@d86736b9f9998c667fd18ce01e16b51d2e97536f -
Branch / Tag:
refs/tags/v1.2.0 - Owner: https://github.com/t-0hmura
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
release.yml@d86736b9f9998c667fd18ce01e16b51d2e97536f -
Trigger Event:
release
-
Statement type: