vastai-core-workflow-a

# Vast.ai Core Workflow A: Instance Provisioning & Job Execution ## Overview Primary workflow for Vast.ai: search for GPU offers, provision an instance, transfer data, execute a training or inference job, collect artifacts, and destroy the instance to stop billing. This is the money-path operation for every Vast.ai user. ## Prerequisites - Completed `vastai-install-auth` setup - Docker image published to a registry (Docker Hub, GHCR, etc.) - SSH key uploaded to Vast.ai - Training data accessible via URL or local path ## Instructions ### Step 1: Search Offers with Filters ```python import subprocess, json def search_offers(gpu_name="RTX_4090", min_vram=24, min_reliability=0.95, max_price=0.50, num_gpus=1): """Search Vast.ai marketplace with specific filters.""" query = ( f"num_gpus={num_gpus} gpu_name={gpu_name} " f"gpu_ram>={min_vram} reliability>{min_reliability} " f"inet_down>200 dph_total<={max_price} rentable=true" ) result = subprocess.run( ["vastai", "search", "offers", query, "--order", "dph_total", "--raw"], capture_output=True, text=True, check=True, ) offers = json.loads(result.stdout) print(f"Found {len(offers)} offers matching criteria") for o in offers[:5]: print(f" ID {o['id']}: {o['gpu_name']} {o['gpu_ram']}GB " f"${o['dph_total']:.3f}/hr reliability={o['reliability2']:.3f}") return offers ``` ### Step 2: Provision an Instance ```python d...