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Quickstart Guide

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Start NIM

This page assumes you have installed and set up Prerequisite Software (Docker, NGC CLI, NGC registry access).

  1. Export NGC_API_KEY variable.
export NGC_API_KEY=<your personal NGC key>

Only Personal API Keys or Service API Keys are supported. Legacy API keys are not supported and will result in a failed docker pull.

  1. NIM container automatically downloads models. To save time and bandwidth it is recommended to provide local cache directory. This way NIM will be able to reuse already downloaded models. Execute following command to setup cache directory.
export LOCAL_NIM_CACHE=~/.cache/nim
mkdir -p "$LOCAL_NIM_CACHE"
sudo chmod 0777 -R "$LOCAL_NIM_CACHE"
  1. Run the NIM container with the following commands.

If you haven’t already, visit the ProteinMPNN NGC page and click Accept Terms under the Governing Terms section before pulling the container. See Prerequisites for details.

docker run -it \
    --runtime=nvidia \
    --gpus='"device=0"' \
    -p 8000:8000 \
    -e NGC_API_KEY \
    -v "$LOCAL_NIM_CACHE":/home/nvs/.cache/nim \
    nvcr.io/nim/ipd/proteinmpnn:latest

This command will start the NIM container and expose port 8000 for the user to interact with the NIM.

  1. Open a new terminal, leaving the terminal open with the just launched service. In the new terminal, wait until the health check end point returns {"status":"ready"} before proceeding. This may take a couple of minutes. You can use the following command to query the health check.
curl http://localhost:8000/v1/health/ready

Python client example

  1. Save following Python example to a file named nim_client.py.
#!/usr/bin/env python3
import requests
import os
import json
from pathlib import Path
def get_reduced_pdb():
    pdb = Path("1R42.pdb")
    if not pdb.exists():
        pdb.write_text(requests.get(f"https://files.rcsb.org/download/{pdb}").text)
    lines = filter(lambda line: line.startswith("ATOM"), pdb.read_text().split("\n"))
    return "\n".join(list(lines)[:200])
r = requests.post(
    url="http://localhost:8000/biology/ipd/proteinmpnn/predict",
    json={
        "input_pdb": get_reduced_pdb(),
        "ca_only": False,
        "use_soluble_model": False,
        "sampling_temp": [0.1],
    },
)
print(r, "Saving to output.fa:\n", r.text[:200], "...")
Path("output.fa").write_text(json.loads(r.text)["mfasta"])
  1. Execute the example.
chmod +x nim_client.py
./nim_client.py
  1. The NIM saves results to the output.fa file in Multi-FASTA format. You can quickly view the file using the following command.
cat output.fa

Shell client example

  1. Save the following Shell example to a file named nim_client.sh.
#!/usr/bin/env bash
set -e
URL=http://localhost:8000/biology/ipd/proteinmpnn/predict
if [ ! -e 1R42.pdb ]; then curl -O https://files.rcsb.org/download/1R42.pdb; fi
pdb=$(cat 1R42.pdb | grep ^ATOM | head -n 200 | awk '{printf "%s\\n", $0}')
request='{
 "input_pdb": "'"$pdb"'",
 "ca_only": false,
 "use_soluble_model": false,
 "sampling_temp": [0.1]
}'
curl -H 'Content-Type: application/json' \
     -d "$request" "$URL"
  1. Execute the example.
chmod +x nim_client.sh
./nim_client.sh
  1. The NIM displays the results to the terminal in JSON format. You can configure the NIM to display the results, scores, and probabilities in the Multi-FASTA output format.