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name: inference description: "Plan and validate OpenFold monomer, multimer, SoloSeq, precomputed-alignment, custom-template, threading, output, relaxation, and acceleration inference workflows." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

OpenFold Inference

Use this sub-skill when the task is to plan, validate, or explain OpenFold prediction commands. It covers run_pretrained_openfold.py for monomer, multimer, SoloSeq/single-sequence, precomputed-alignment, custom-template, long-sequence, output, relaxation, and acceleration planning, plus thread_sequence.py for threading one sequence onto one template mmCIF.

Route Quickly

• Read references/cli-reference.md for positional arguments, flags, presets, database/tool differences, output flags, and command patterns.
• Read references/inference-workflows.md for mode selection and workflows for monomer, multimer, SoloSeq, precomputed alignments, custom templates, long sequences, and threading.
• Read references/troubleshooting.md when inference fails because of missing extensions, weights, databases, binaries, precomputed layouts, template mismatches, SoloSeq length, acceleration dependencies, or relaxation.
• Use scripts/build_inference_command.py to build dry-run commands for monomer, multimer, SoloSeq, and threading without importing OpenFold or executing inference.
• Use scripts/validate_inference_inputs.py to inspect FASTA files, template mmCIF directories, precomputed alignment or embedding layouts, SoloSeq length limits, threading inputs, and optional checkpoint paths.

Boundaries

• Route OpenFold installation, CUDA/PyTorch/OpenMM, parameters, sequence databases, external binaries, and optional backend readiness to ../installation-assets/.
• Route alignment/database/cache production and deep alignment layout conversion to ../data-preparation/.
• Route low-level config internals, model APIs, checkpoint conversion, tensor shapes, and acceleration implementation details to ../model-apis/.
• Route training, fine-tuning, Lightning, and DeepSpeed training commands to ../training/.

Verified OpenFold Facts

• run_pretrained_openfold.py takes required positionals fasta_dir and template_mmcif_dir, writes under --output_dir, and accepts --use_precomputed_alignments to skip alignment generation.
• Monomer inference uses HHSearch/PDB70 for template search; multimer inference uses presets such as model_1_multimer_v3 and PDB SeqRes with HMMSearch/HMBuild plus UniProt and UniRef30 inputs.
• SoloSeq uses seq_model_esm1b_ptm, ESM-1b embeddings, a SoloSeq OpenFold checkpoint, optional HHSearch template hits, and a 1022-residue sequence limit.
• thread_sequence.py accepts one FASTA file and one template mmCIF file, expects exactly one query sequence, and uses --template_id plus --chain_id to select the template chain.
• Current CLI help may fail in incomplete environments if the attn_core_inplace_cuda extension is missing; the bundled helper scripts avoid OpenFold imports and should still work.