orca-mlips 1.0.0

MLIP plugins for ORCA ExtTool (UMA, ORB, MACE, AIMNet2)

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.

The model server starts automatically and stays resident in memory, so repeated calls during optimization are fast.

Requires Python 3.9 or later.

Quick Start (Default = UMA)

1. Install PyTorch for your environment (CUDA/CPU).

pip install torch==2.8.0 --index-url https://download.pytorch.org/whl/cu129

2. Install the package with UMA profile. If you need ORB/MACE/AIMNet2, use orca-mlips[orb]/orca-mlips[mace]/orca-mlips[aimnet2].

pip install "orca-mlips[uma]"

3. Log in to Hugging Face for UMA model access. (Not required for ORB/MACE/AIMNet2)

huggingface-cli login

4. Use in an ORCA input file. If you use ORB/MACE/AIMNet2, use ProgExt "orb"/ProgExt "mace"/ProgExt "aimnet2". For detailed ORCA External Tool / ExtOpt usage, 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

Note: Run uma --list-models to see available models. If the uma alias conflicts in your environment, use orca-mlips-uma instead.

Additional examples: examples/cla_hess_uma.inp + examples/cla_uma.inp, examples/sn2_hess_orb.inp + examples/sn2_orb.inp, examples/water_hess_mace.inp + examples/water_mace.inp, examples/cla_hess_aimnet2.inp + examples/cla_aimnet2.inp

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:

1. dump Hessian with --dump-hessian <file> in step 1,
2. 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
...
*

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 non-zero (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 conflict at dependency level (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 login once.
• 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.

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 — Use ProgExt "orca-mlips-uma" to avoid alias conflicts.
• ProgExt "aimnet2" runs the wrong plugin — Use ProgExt "orca-mlips-aimnet2" to avoid alias conflicts.
• uma command 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 uma in the ORCA input.

Citation

If you use this package, please cite:

@software{ohmura2026orcamlips,
  author       = {Ohmura, Takuto},
  title        = {orca-mlips},
  year         = {2026},
  month        = {2},
  version      = {1.0.0},
  url          = {https://github.com/t-0hmura/orca-mlips},
  license      = {MIT},
  doi          = {10.5281/zenodo.18691881}
}

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