"""Inspect local inference assets; never load pickle metadata, model weights, or a robot SDK."""
from pathlib import Path
import argparse,hashlib,json

def check(model,checkpoint,resources=None,cell_data=None,verify_hashes=False,checkpoint_only=False):
    root=Path(checkpoint);required=['model.safetensors'];result={'model':model,'checkpoint_name':root.name,'hashes_verified':False,'resources_checked':False}
    if model=='flux':required+=['config.json','manifest.json']
    else:required+=['assets/umi_v3/norm_stats.json']
    for name in required:
        p=root/name
        if not p.is_file() or p.stat().st_size==0:raise ValueError('Missing/empty checkpoint asset: '+name)
    if model=='flux':
        c=json.loads((root/'config.json').read_text());m=json.loads((root/'manifest.json').read_text())
        if c.get('action_dim')!=20 or c.get('chunk_size')!=32 or c.get('torch_dtype')!='bfloat16':raise ValueError('Expected 20-D / 32-step BF16 UMI export')
        if m.get('kind')!='policy_export' or m.get('format_version')!=1:raise ValueError('Not a policy-export manifest')
        if not checkpoint_only:
            if resources is None:raise ValueError('FLUX needs --resources for frozen encoder assets')
            if not (Path(resources)/'video_vae.safetensors').is_file() or not (Path(resources)/'text_encoder').is_dir():raise ValueError('Missing FLUX VAE or text encoder')
            result['resources_checked']=True
        if verify_hashes:
            for name in ['config.json','model.safetensors']:
                h=hashlib.sha256()
                with (root/name).open('rb') as f:
                    while block:=f.read(8*1024*1024):h.update(block)
                if h.hexdigest()!=m.get('sha256',{}).get(name):raise ValueError('Manifest hash mismatch: '+name)
            result['hashes_verified']=True
    else:
        stats=json.loads((root/'assets/umi_v3/norm_stats.json').read_text())
        if not isinstance(stats,dict) or not stats:raise ValueError('Empty/invalid normalization statistics')
        result['optimizer_required_for_inference']=False
    if cell_data:
        for name in ['E_left.npy','E_right.npy','E_from_urdf.json']:
            if not (Path(cell_data)/name).is_file():raise ValueError('Missing cell extrinsic: '+name)
    result.update(status='passed_inventory_checks',model_bytes=(root/'model.safetensors').stat().st_size,weights_loaded=False)
    return result

def main():
    p=argparse.ArgumentParser(description=__doc__);p.add_argument('--model',choices=['flux','pi05'],required=True);p.add_argument('--checkpoint',required=True);p.add_argument('--resources');p.add_argument('--cell-data');p.add_argument('--verify-hashes',action='store_true');p.add_argument('--checkpoint-only',action='store_true',help='Check checkpoint without external encoders');a=p.parse_args()
    try:print(json.dumps(check(a.model,a.checkpoint,a.resources,a.cell_data,a.verify_hashes,a.checkpoint_only),indent=2))
    except (ValueError,OSError,json.JSONDecodeError) as exc:p.exit(2,str(exc)+'\n')
if __name__=='__main__':main()