OpenFold2 NIM

Predict a single protein-chain structure from an amino-acid sequence, with optional A3M multiple sequence alignments and mmCIF templates. Use this guide for basic hosted/local NIM use; load supplemental files only when the task needs deeper context:

• references/api.md: exact endpoints, schemas, Docker flags, response fields.
• references/science.md: model scope, strengths, limitations, and handoffs.
• references/parameters.md: MSA, template, model-selection, and relax effects.
• references/validation.md: artifact and scientific sanity checks.
• references/examples.md: compact hosted/local payload patterns.

Choose Mode

Ask only when context is unclear:

Hosted NVIDIA API or local Docker NIM?

• Hosted URL: https://health.api.nvidia.com/v1/biology/openfold/openfold2/predict-structure-from-msa-and-template
• Local URL: http://localhost:8000/biology/openfold/openfold2/predict-structure-from-msa-and-template
• Local readiness: http://localhost:8000/v1/health/ready

Mode difference: hosted and local use the same prediction path except local does not include /v1/. Hosted requests use Authorization: Bearer $NGC_API_KEY; local inference requests use no auth header after readiness.

Auth And Environment

Do not print API keys. Confirm they exist with shell tests, not echoes.

Hosted needs NGC_API_KEY in the request header. Supported local Docker startup uses NGC_API_KEY, or NVIDIA_API_KEY as a fallback, plus LOCAL_NIM_CACHE. A repo-root .env file may be sourced as a local override.

Local Docker

Use the official OpenFold2 NIM image and mount LOCAL_NIM_CACHE at /opt/nim/.cache. Current docs recommend at least 80 GB disk, 64 GB system RAM, 8 CPU cores, and one supported GPU; the container is roughly 55 GB and first startup downloads about 10 GB of model parameters.