| import asyncio,json |
| from pathlib import Path |
| import torch |
| from coreai_mini import AmosMini |
| async def main(): |
| def forbidden(*a,**kw):raise AssertionError('PyTorch neural execution is forbidden in runtime smoke') |
| torch.nn.Linear.forward=forbidden;torch.nn.Embedding.forward=forbidden;torch.nn.Conv2d.forward=forbidden |
| root=Path('bundles/amos-1-mini-CoreAI');m=await AmosMini.load(root) |
| out=await m.request({'state':'Please refund the duplicate charge.','questions':{'refund':{'type':'noul','instructions':'Is a refund requested?'}}}) |
| assert out['answers']['refund']['noul']>0.5,out |
| from PIL import Image |
| image_result=await m.predict('A red image.',[{'type':'region','text':'Point to the red area.'}],[Image.new('RGB',(360,240),'red')]) |
| assert image_result[0]['type']=='region' |
| try:await m.predict('word '*1000,[{'type':'noul','text':'Is there text?'}]) |
| except ValueError:capacity_guard=True |
| else:raise AssertionError('Over-capacity request was accepted') |
| (root/'runtime-smoke.json').write_text(json.dumps({'passed':True,'pytorch_neural_execution_disabled':True,'capacity_guard':capacity_guard,'result':out,'image_result':image_result},indent=2)) |
| print(out) |
| if __name__=='__main__':asyncio.run(main()) |
|
|
