Lambda Labs for Enterprise AI: GPU Infrastructure & Integration

import requests
import os
import json

LAMBDA_API_KEY = os.getenv("LAMBDA_API_KEY")
LAMBDA_API_URL = "https://cloud.lambdalabs.com/api/v1"

def launch_lambda_gpu_instance(instance_type_name: str, region_name: str, ssh_key_name: str) -> dict:
  """
  Launches a GPU instance on Lambda Labs Cloud programmatically.
  """
  headers = {
      "Authorization": f"Bearer {LAMBDA_API_KEY}",
      "Content-Type": "application/json"
  }

  payload = {
      "region_name": region_name,
      "instance_type_name": instance_type_name,
      "ssh_key_names": [ssh_key_name],
      "file_system_names": ["esaholic-datasets-nvme"],
      "name": "h100-fine-tune-worker-01"
  }

  response = requests.post(
      f"{LAMBDA_API_URL}/instance-operations/launch",
      headers=headers,
      json=payload
  )

  if response.status_code == 200:
      return response.json()
  else:
      raise RuntimeError(f"Lambda API Launch Error: {response.status_code} - {response.text}")

if __name__ == "__main__":
  # Launch 1x NVIDIA H100 SXM5 instance in us-tx-1 region
  instance_type = "gpu_1x_h100_sxm5"
  region = "us-tx-1"
  ssh_key = "esaholic-prod-key"

  result = launch_lambda_gpu_instance(instance_type, region, ssh_key)
  print("Lambda Instance Launch Result:", json.dumps(result, indent=2))