The official Python SDK for the VectorLay API
Project description
VectorLay Python SDK
The official Python SDK for the VectorLay API.
Installation
pip install vectorlay
Quick Start
import vectorlay
client = vectorlay.Client(api_key="vl_your_api_key")
# List available GPUs
gpus = client.gpus.list()
# Deploy a cluster
cluster = client.clusters.create(
name="my-inference",
gpu_type="h100",
replicas=2,
container="vllm/vllm-openai:latest",
env={"MODEL": "meta-llama/Llama-3-8B"},
container_port=8000,
)
# Wait for it to be ready
cluster = client.clusters.wait_for_status(cluster.id)
print(f"Cluster running at: {cluster.endpoint_url}")
# Scale up
client.clusters.scale(cluster.id, replicas=4)
# Create a VM
vm = client.vms.create(
name="dev-box",
ssh_key_ids=["your-ssh-key-id"],
gpu_type="rtx-4090",
gpu_count=1,
disk_size_gb=100,
)
Async Usage
import asyncio
import vectorlay
async def main():
async with vectorlay.AsyncClient(api_key="vl_your_api_key") as client:
clusters = await client.clusters.list()
print(clusters)
asyncio.run(main())
Configuration
The client accepts these parameters:
| Parameter | Env Variable | Default |
|---|---|---|
api_key |
VECTORLAY_API_KEY |
Required |
base_url |
VECTORLAY_BASE_URL |
https://api.vectorlay.com |
timeout |
— | 60.0 seconds |
max_retries |
— | 2 |
License
MIT
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