Skills

Genmol Nim

Generate novel drug-like molecules using the GenMol NIM microservice.

Install

npx skills add NVIDIA/skills --skill genmol-nim -g -a claude-code -y
Repository
NVIDIA/skills3.8k
Category
DevOps
Updated
5d ago
License
Apache-2.0 AND CC-BY-4.0
Context cost
Lightabout 1,235 tokens
Runs scripts
No, instructions only

What it does

Generate novel drug-like molecules using the GenMol NIM microservice. Use for de novo generation, scaffold decoration, motif extension, lead optimization, SAFE notation, QED or LogP ranking, hosted NVIDIA API calls, or local Docker deployment. GenMol takes SAFE notation in the smiles field, not ordinary SMILES.

GenMol NIM

Generate drug-like molecules with GenMol. Use this guide for first-pass hosted and local usage; load supplemental files only when needed:

  • references/api.md: endpoints, schema, Docker flags, response fields.
  • references/science.md: use cases, strengths, limits, and handoffs.
  • references/parameters.md: SAFE patterns and tuning effects.
  • references/validation.md: chemical and artifact checks.
  • references/examples.md: compact request patterns.

Choose Mode

Ask only when context is unclear:

Hosted NVIDIA API or local Docker NIM?

  • Hosted: https://health.api.nvidia.com/v1/biology/nvidia/genmol/generate
  • Local: http://localhost:8000/generate

Hosted requests use Authorization: Bearer $NGC_API_KEY. For local Docker, authenticate image pulls with docker login nvcr.io using NGC_API_KEY (or NVIDIA_API_KEY via the preflight). Pass -e NGC_API_KEY into the container for entitlement checks and first-run model downloads. Local inference requests use no auth header after readiness, so bind the published port to loopback with -p 127.0.0.1:8000:8000. Warm-cache key-free startup varies by image version and should not be assumed.

Local Docker

Use credentials already supplied in the shell environment or injected by a secret manager. Do not load credential files, print keys, or enable shell tracing. For local setup answers, include this sequence: env preflight, docker login with --password-stdin, docker run, readiness loop, then a no-auth localhost request. Do not invent a cache default or drop the NVIDIA_API_KEY fallback.

Before executing local setup, explain that registry authentication sends the key to the NVIDIA registry at https://nvcr.io and first-run model downloads use about 20 GB in LOCAL_NIM_CACHE. Execute deployment only when the user requests it; for a setup guide, provide the commands without running them.

Read the whole SKILL.md on GitHub

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