Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
日本語の概要は準備中です。原文の説明を表示しています。
Run DiffDock molecular docking via NVIDIA NIM to predict small-molecule binding poses against protein targets. Use for DiffDock, molecular docking, ligand docking, blind docking, SMILES or SDF ligands, ranked poses, confidence scores, hosted NVIDIA API, or local Docker deployment.
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Predict protein-ligand binding poses with blind docking. Use this guide for first-pass hosted/local usage; load supplemental files only when needed:
references/api.md: exact hosted/local endpoints, schemas, Docker flags.references/science.md: docking use cases, limits, and handoffs.references/parameters.md: ligand formats, pose counts, diffusion controls.references/validation.md: receptor, ligand, pose, and confidence checks.references/examples.md: compact hosted/local and pose-saving patterns.Ask only when context is unclear:
Hosted NVIDIA API or local Docker NIM?
https://health.api.nvidia.com/v1/biology/mit/diffdockhttp://localhost:8000/molecular-docking/diffdock/generateThe hosted and local paths differ. Local has no /v1/ prefix and uses the
/molecular-docking/ route. 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.
For the exact local preflight (.env load, NVIDIA_API_KEY fallback,
LOCAL_NIM_CACHE, NVIDIA_VISIBLE_DEVICES=0, --shm-size=2G, both --ulimit
flags, docker login, and the docker run for nvcr.io/nim/mit/diffdock:2.2.0),
copy the command block in references/api.md under
Docker Reference verbatim.
Readiness:
until curl -sf http://localhost:8000/v1/health/ready; do sleep 5; done
Protein receptor must be ATOM records only. Strip headers, water, and HETATM.
from pathlib import Path
raw_pdb = Path("protein.pdb").read_text()
protein = "\n".join(line for line in raw_pdb.splitlines() if line.startswith("ATOM"))
if not protein:
raise ValueError("protein.pdb has no ATOM records")
Ligand options:
ligand = "CC(=O)OC1=CC=CC=C1C(=O)O"; ligand_file_type = "txt".ligand = Path("ligand.sdf").read_text(); ligand_file_type = "sdf".ligand_file_type = "mol2".Do not use "smiles" as ligand_file_type; SMILES is "txt".
import os
import requests
HOSTED = True
url = (
"https://health.api.nvidia.com/v1/biology/mit/diffdock"
if HOSTED else "http://localhost:8000/molecular-docking/diffdock/generate"
)
headers = {"Content-Type": "application/json"}
if HOSTED:
headers["Authorization"] = f"Bearer {os.getenv('NGC_API_KEY')}"
payload = {
"protein": protein,
"ligand": ligand,
"ligand_file_type": ligand_file_type,
"num_poses": 10,
"time_divisions": 20,
"steps": 18,
"save_trajectory": False,
}
response = requests.post(url, headers=headers, json=payload, timeout=300)
response.raise_for_status()
result = response.json()
ligand_positions and position_confidence are parallel ranked lists.
position_confidence[0] is the rank-1 pose confidence.
Save the ranked pose SDFs using the snippet in
references/examples.md under Save Ranked Poses.
View pose SDF files with the receptor in PyMOL, ChimeraX, or UCSF Chimera. For
pose sanity checks and confidence caveats, read references/validation.md.
num_poses: 100. Max time_divisions: 20. Max steps: 18.422: invalid ligand_file_type, invalid SMILES/SDF, or no ATOM records./v1/.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
日本語の概要は準備中です。原文の説明を表示しています。
Customize NVIDIA Nemotron Voice Agent's Generic Pipecat example for healthcare appointment, five-field patient intake, or custom tool-calling workflows without a separate backend.
日本語の概要は準備中です。原文の説明を表示しています。
Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras; VIOS records clips, AMC ingests them, then runs calibration.
日本語の概要は準備中です。原文の説明を表示しています。
Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.
日本語の概要は準備中です。原文の説明を表示しています。
Calibrates pre-recorded `cam_*.mp4` datasets through the AutoMagicCalib REST API. Use for user-supplied local MP4s; route live RTSP streams to `amc-run-rtsp-calibration`.
日本語の概要は準備中です。原文の説明を表示しています。
Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API key.
日本語の概要は準備中です。原文の説明を表示しています。