---

name: omega-fold description: "Use OmegaFold for protein structure prediction from FASTA to PDB, including CLI inference, FASTA/PDB handling, and Python model API inspection." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

OmegaFold

Use this repo skill when a task involves OmegaFold, de novo protein structure prediction from amino-acid FASTA input, OmegaFold PDB outputs, the omegafold CLI, or the Python APIs omegafold.make_config, omegafold.OmegaFold, and omegafold.pipeline.

OmegaFold is release inference code. It is not a training, fine-tuning, dataset-building, model-serving, or general PDB-editing toolkit.

Start Here

1. For command-line prediction from FASTA to PDB, read inference-cli.
2. For FASTA validation, pseudo-MSA tensors, PDB output names, and confidence/B-factor interpretation, read data-and-outputs.
3. For programmatic model construction, configs, forward inputs/outputs, and API debugging, read model-api.
4. For installation, dependency, Python, Torch, CUDA/MPS, and smoke-check guidance shared across routes, read install and environment.
5. For cross-cutting failures, read root troubleshooting, then route to the nearest sub-skill troubleshooting file.

Route by Task

User task	Read
Build or validate an omegafold INPUT_FILE.fasta OUTPUT_DIRECTORY command	sub-skills/inference-cli/SKILL.md
Decide --model, --device, --weights_file, --subbatch_size, or --num_cycle	sub-skills/inference-cli/references/inference-workflow.md
Check whether the CLI is installed without downloading weights	sub-skills/inference-cli/scripts/omegafold_cli_smoke.py
Explain accepted FASTA syntax, ambiguous residues, sequence sorting, or output PDB names	sub-skills/data-and-outputs/references/data-formats.md
Exercise pipeline.fasta2inputs or pipeline.save_pdb safely	sub-skills/data-and-outputs/scripts/inspect_fasta_pipeline.py
Instantiate OmegaFold, call make_config, load weights, or inspect forward	sub-skills/model-api/references/api-reference.md
Inspect API signatures/configs without loading checkpoints	sub-skills/model-api/scripts/inspect_model_api.py
Diagnose install/import/backend issues before choosing a route	references/install-and-environment.md and references/troubleshooting.md

Minimal Install Expectations

OmegaFold distribution metadata is OmegaFold and the import module is omegafold. The package exposes the console script omegafold=omegafold.__main__:main.

For legacy-compatible installations, prefer Python 3.8, 3.9, or 3.10 with Biopython and a Torch build compatible with the target accelerator. The release requirements pin torch==1.12.0+cu113; when using that stack, keep numpy<2 to avoid NumPy ABI warnings or import/runtime failures.

Safe import check:

python - <<'PY'
import omegafold
print(omegafold.make_config(1).struct_embedder)
print(omegafold.make_config(2).struct_embedder)
PY

Safe CLI check:

omegafold --help

Use the bundled scripts/check_omega_fold_environment.py when you need a single no-download environment report before choosing a sub-skill.

Safety Rules

• omegafold --help, bundled helper scripts, and API signature inspection are safe no-download checks.
• Full omegafold INPUT_FILE.fasta OUTPUT_DIRECTORY inference may download model weights, allocate a large model, use GPU/MPS/CPU resources, and take substantial time.
• Do not run full inference unless the user accepts downloads/runtime or provides a local checkpoint through --weights_file.
• Do not assume FASTA file order equals output order; OmegaFold sorts records by sequence length before processing.
• Do not interpret OmegaFold PDB B-factors as experimental crystallographic B-factors; the CLI writes per-residue confidence multiplied by 100 into the B-factor field.
• Do not present random no-weight outputs as meaningful predictions; load the matching model 1 or model 2 checkpoint before inference.

Repository Facts

• Primary workflow: de novo structure prediction from one or more FASTA sequences to one PDB per sequence.
• Public CLI: omegafold INPUT_FILE.fasta OUTPUT_DIRECTORY [options].
• Public Python entry points: omegafold.make_config, omegafold.OmegaFold, omegafold.pipeline.fasta2inputs, omegafold.pipeline.save_pdb.
• Model ids: 1 and 2 only.
• Device auto-selection: CUDA, then MPS, then CPU.
• Provenance and staleness baseline: references/repo-provenance.md.