boltz2-nim
Use Boltz2 NIM for biomolecular structure prediction and binding affinity. Invoke for Boltz2, protein structures, protein-ligand/DNA/RNA complexes, SMILES or CCD ligands, pIC50/IC50 affinity scoring, mmCIF output, hosted NVIDIA API calls, or local Docker deployment.
How do I install this agent skill?
npx skills add https://github.com/nvidia-bionemo/bionemo-agent-toolkit --skill boltz2-nimIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The Boltz2 NIM skill provides biomolecular structure and binding affinity prediction via NVIDIA's API or local Docker deployment. The skill follows security best practices for credential handling, utilizing environment variables for API keys rather than hardcoding secrets. All external resources, including the Docker registry and API endpoints, are hosted by the official vendor, and no malicious patterns or obfuscation were detected.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
What does this agent skill do?
Boltz2 NIM
Predict biomolecular structures and optional ligand affinity. Use this guide for first-pass hosted/local usage; load supplemental files only when needed:
references/api.md: exact endpoints, schemas, Docker flags, response fields.references/science.md: purpose, strengths, limitations, and handoffs.references/parameters.md: prediction, sampling, MSA, template, affinity tuning.references/validation.md: mmCIF, confidence, affinity, and chemistry checks.references/examples.md: compact hosted/local payload patterns.
Instructions
Read credentials from the environment only when needed. Check presence with
bool(os.getenv("NGC_API_KEY")); keep key values and Authorization headers out of
terminal output, logs, saved artifacts, and the final response. Avoid environment
dumps when diagnosing authentication. If the hosted key is absent, report the
missing variable before submitting a request.
Choose Mode
Ask only when context is unclear:
Hosted NVIDIA API or local Docker NIM?
- Hosted:
https://health.api.nvidia.com/v1/biology/mit/boltz2/predict - Local:
http://localhost:8000/biology/mit/boltz2/predict
Hosted requests use Authorization: Bearer $NGC_API_KEY. Supported local Docker
startup uses NGC_API_KEY (or NVIDIA_API_KEY via the preflight) for
registry login, entitlement checks, and first-run model downloads; pass it
into the container with -e NGC_API_KEY. Local inference requests use no
auth header after readiness. Warm-cache key-free startup varies by
image/version and should not be assumed.
Local Docker
For local setup answers, copy the preflight below before docker login,
docker run, readiness, and the no-auth local request. Do not invent a cache
default or drop the .env load or NVIDIA_API_KEY fallback.
set -a
[ -f .env ] && . ./.env
set +a
if [ -z "${NGC_API_KEY:-}" ] && [ -n "${NVIDIA_API_KEY:-}" ]; then
export NGC_API_KEY="$NVIDIA_API_KEY"
fi
: "${NGC_API_KEY:?Set NGC_API_KEY or NVIDIA_API_KEY}"
: "${LOCAL_NIM_CACHE:?Set LOCAL_NIM_CACHE}"
echo "$NGC_API_KEY" | docker login nvcr.io --username '$oauthtoken' --password-stdin
mkdir -p "${LOCAL_NIM_CACHE}"
chmod 755 "${LOCAL_NIM_CACHE}"
docker run --rm --name boltz2 --gpus all \
--shm-size=16G \
-e NGC_API_KEY \
-v "${LOCAL_NIM_CACHE}:/opt/nim/.cache" \
-p 8000:8000 \
nvcr.io/nim/mit/boltz2:1.6.0
Readiness:
until curl -sf http://localhost:8000/v1/health/ready; do sleep 5; done
First startup downloads about 30 GB of model weights.
Examples
Prediction Request
import os
import requests
HOSTED = True
url = (
"https://health.api.nvidia.com/v1/biology/mit/boltz2/predict"
if HOSTED else "http://localhost:8000/biology/mit/boltz2/predict"
)
headers = {"Content-Type": "application/json"}
if HOSTED:
api_key = os.getenv("NGC_API_KEY")
if not api_key:
raise SystemExit("NGC_API_KEY is required for the hosted API")
headers["Authorization"] = f"Bearer {api_key}"
payload = {
"polymers": [{
"id": "A",
"molecule_type": "protein",
"sequence": "MTEYKLVVVGACGVGKSALTIQLIQNHFVDEYDPT",
}],
"recycling_steps": 3,
"sampling_steps": 50,
"diffusion_samples": 1,
"step_scale": 1.638,
"output_format": "mmcif",
}
response = requests.post(url, headers=headers, json=payload, timeout=300)
response.raise_for_status()
result = response.json()
Payload essentials:
- Protein polymer:
{"molecule_type": "protein", "sequence": "..."}. - DNA/RNA polymer: add another polymer with
molecule_type"dna"or"rna". - Ligand by SMILES:
{"id": "L1", "smiles": "CC(=O)OC1=CC=CC=C1C(=O)O"}. - Ligand by CCD:
{"id": "L1", "ccd": "ATP"}. - Affinity: set
"predict_affinity": Trueon exactly one ligand; reportaffinity_pic50,affinity_pred_value, andaffinity_probability_binary. - Precomputed A3M MSA goes under the protein polymer. The A3M record uses
alignment,format, andrank; do not use a staledatafield.
protein_with_msa = {
"id": "A",
"molecule_type": "protein",
"sequence": "MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPT",
"msa": {"msa_search": {"a3m": {
"alignment": ">query\nMTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPT",
"format": "a3m",
"rank": 0,
}}},
}
Save And Report Output
Save every .cif artifact and read the confidence/affinity fields using the
snippet in references/examples.md under Save
Structures And Affinity. Visualize in PyMOL, ChimeraX, or UCSF Chimera. For
confidence/affinity sanity checks, read references/validation.md.
Limits And Troubleshooting
- Polymers/request: 12. Ligands/request: 20. Chain length: 4096 residues.
- Affinity prediction supports one ligand per request and adds runtime.
422: invalid sequence, invalid CCD/SMILES, malformed MSA, or multiple affinity ligands.- Local URL/auth: local path has no hosted auth header; wait on
/v1/health/ready. - Local startup: use
--gpus all,--shm-size=16G, and the/opt/nim/.cachemount.
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/nvidia-bionemo/bionemo-agent-toolkit/boltz2-nim">View boltz2-nim on skillZs</a>