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vastai-sdk
The vastai SDK is a Python library for programmatically managing GPU instances, storage volumes, serverless endpoints, and billing operations on the Vast.ai platform. Use this skill when building applications that need to provision GPU compute resources, search available offers, control instance lifecycles, manage interruptible spot rentals, or integrate Vast.ai infrastructure management into automated workflows.
Install in Claude Code
Copygit clone --depth 1 https://github.com/vast-ai/vast-cli /tmp/vastai-sdk && cp -r /tmp/vastai-sdk/vastai_sdk ~/.claude/skills/vastai-sdkThen start a new Claude Code session; the skill loads automatically.
Definition
SKILL.md
# Vast.ai Python SDK (`vastai` / `vastai_sdk`)
The `vastai` package provides a Python SDK for managing GPU instances, volumes, serverless endpoints, and billing on Vast.ai. The `vastai_sdk` package is a backward-compatibility shim that re-exports `vastai`.
## Installation
```bash
pip install vastai
```
For serverless and async support:
```bash
pip install "vastai[serverless]"
```
## Authentication
The SDK reads the API key from `~/.vast_api_key` by default. You can also pass it explicitly:
```python
from vastai import VastAI
vast = VastAI() # reads ~/.vast_api_key
vast = VastAI(api_key="YOUR_API_KEY") # explicit key
```
Get your API key from https://console.vast.ai/manage-keys/
## Backward Compatibility
The old `vastai_sdk` import still works:
```python
from vastai_sdk import VastAI # equivalent to: from vastai import VastAI
```
## VastAI Class (High-Level SDK)
```python
from vastai import VastAI
vast = VastAI(api_key=None, server_url=None, retry=3, raw=False, quiet=False)
```
### Instance Management
```python
# List all your instances
instances = vast.show_instances()
# Get a single instance
instance = vast.show_instance(id=12345)
# Search GPU offers
offers = vast.search_offers(query='gpu_name=RTX_4090 num_gpus>=4 reliability>0.99')
# Create an instance from an offer
result = vast.create_instance(id=<offer_id>, image="pytorch/pytorch:latest", disk=50)
# ...as a jupyter instance on a direct connection
result = vast.create_instance(id=<offer_id>, image="pytorch/pytorch:latest", disk=50,
jupyter=True, direct=True, jupyter_lab=True)
# Lifecycle
vast.start_instance(id=12345)
vast.stop_instance(id=12345)
vast.reboot_instance(id=12345)
vast.destroy_instance(id=12345)
# Label an instance
vast.label_instance(id=12345, label="my-training-run")
# Get SSH connection string
ssh_url = vast.ssh_url(id=12345) # returns "ssh -p PORT user@host"
scp_url = vast.scp_url(id=12345) # returns scp-compatible URL
```
### Interruptible (spot) rentals
Interruptible (spot) instances are priced below on-demand instances, but can be interrupted at any time by another user with a lower bid. Note: `vast.search_offers(type='bid', ...)` exposes `min_bid`, but `vast.create_instance(...)` defaults to **on-demand at `dph_total`** unless you pass `bid_price=<floor>`. Always pass `bid_price` after a `type='bid'` search, otherwise the instance will be rented as an on-demand instance/price instead of as an interruptible.
When outbid, the instance moves to `stopped` (not destroyed) and storage charges continue. Resume by raising the bid via `vast.change_bid(id=..., price=...)`.
### Search
```python
# Search GPU offers (use help(vast.search_offers) for full query syntax)
offers = vast.search_offers(query='gpu_name=RTX_3090 num_gpus>=2')
# Search volume offers
volumes = vast.search_volumes(query='...')
# Search network volumes
net_vols = vast.search_network_volumes()
# Search templates
templates = vast.search_templates()
# Search invoices
invoices = vast.search_invoices()
```
### Data Transfer
```python
# copy() takes vast URLs: "[C.|V.]id:path", "cloud_service[.id]:path", or "local:path"
vast.copy("local:./data/", "C.12345:/workspace/data/") # Local → instance
vast.copy("C.12345:/workspace/results/", "local:./out/") # Instance → local
vast.copy("12345:/workspace/", "67890:/workspace/") # Instance → instance (legacy format)
vast.copy("s3.101:/data/", "C.12345:/workspace/") # Cloud service → instance
vast.copy("V.1234:/file", "C.5678:/workspace/") # Volume → instance
vast.copy("V.1234:/file", "s3.101:/workspace/") # Volume → cloud service
vast.cancel_copy(dst_id=12345) # Cancel an in-progress copy
# Cloud sync via a saved cloud connection (see the UI settings page for connection IDs)
vast.cloud_copy(src="./data", dst="s3://bucket/path", instance=12345,
connection=<conn_id>, transfer="Instance To Cloud")
vast.cancel_sync(dst_id=12345)
```
Volume copy is currently only supported for copying to other volumes, instances, or cloud services, not local. Do not use `/root` or `/` as a destination directory — it breaks ssh permissions on the instance and future copies fail. See https://vast.ai/docs/gpu-instances/data-movement#constraints.
### Serverless Deployments
```python
# List all deployments
deployments = vast.show_deployments()
# Get a deployment
deployment = vast.show_deployment(id=42)
# Delete a deployment
vast.delete_deployment(id=42)
```
### Machine Management (Hosting)
```python
machines = vast.show_machines()
machine = vast.show_machine(id=10)
vast.list_machine(id=10, price_gpu=0.30)
vast.unlist_machine(id=10)
```
### SSH Keys
```python
keys = vast.show_ssh_keys()
vast.create_ssh_key(ssh_key="ssh-rsa AAAA...")
vast.delete_ssh_key(id=5)
```
### Team Management
```python
members = vast.show_members()
vast.invite_member(email="user@example.com", role="developer")
vast.remove_member(id=7)
```
## SyncClient (Low-Level Sync)
`SyncClient` provides typed, synchronous access to GPU offers and instances.
```python
from vastai import SyncClient
client = SyncClient(api_key="YOUR_API_KEY") # or reads ~/.vast_api_key
# Search offers with structured filters
offers = client.search(
num_gpus=2,
gpu_name="RTX_4090",
min_reliability=0.99,
max_dph_total=2.0,
)
# Create an instance (SyncClient takes an InstanceConfig, not loose kwargs)
from vastai.data.instance import InstanceConfig
instance = client.create_instance(
offer_id=<id>,
config=InstanceConfig(image="pytorch/pytorch:latest", disk=50),
)
# List your instances
instances = client.show_instances() # returns list[SyncInstance]
# Destroy an instance
client.destroy_instance(instance_or_id=12345)
```
## AsyncClient (Low-Level Async)
`AsyncClient` provides async access to GPU offers and instances. Use as an async context manager.
```python
import asyncio
from vastai import AsyncClienMore from this repository