Quickstart & Execution Recipes

Standard usage patterns and rapid prototyping code

Basic Execution Recipe

import ameva_runtime as ameva
from ameva_runtime import vulkan

# 1. Execute LLM inference directly with optimal on-device hardware dispatch
result = ameva.run(
    model="qwen2.5-0.5b",
    prompt="Space in Korean is:",
    max_tokens=32
)
print(f"Generated text: {result.text}")
print(f"Hardware backend: {result.backend_used} ({result.tokens_per_second:.2f} t/s)")

# 2. Hardware diagnostic inspection via Vulkan engine
doc = vulkan.Doctor()
report = doc.run_self_test(verbose=False)
print(f"GPU Target: {report.device_name} (Passed: {report.passed_stages}/{report.total_stages})")