"""Adapter for the inference(prompt, image, task=...) API shown in module DR.

loader is a deployment-pinned callable returning the already loaded model.
No guessed vendor import, checkpoint download, remote code execution flag or CUDA map.
"""
import importlib
import re

def create(config):
    if not isinstance(config,dict) or not isinstance(config.get('loader'),str) or not re.fullmatch(r'[A-Za-z_]\w*(?:\.[A-Za-z_]\w*)*:[A-Za-z_]\w*',config['loader']):
        raise ValueError('loader must name a deployment-provided module:callable')
    mapping=config.get('task_mapping')
    if not isinstance(mapping,dict) or not mapping or any(not isinstance(value,str) or not value.strip() for value in mapping.values()):
        raise ValueError('task_mapping must contain deployment-validated model tasks')
    if 'dense_feedback' in mapping:
        raise ValueError('dense feedback requires a deployment-provided multi-frame adapter; this adapter accepts a single image')
    if set(mapping)-{'plan','shelf','localize3d'}:
        raise ValueError('unsupported capability in task_mapping')
    if not isinstance(config.get('model'),dict):
        raise ValueError('model must contain deployment-provided loading configuration')
    module,name=config['loader'].split(':',1)
    try:loader=getattr(importlib.import_module(module),name)
    except (ImportError,AttributeError) as ex:
        raise ValueError('deployment model loader unavailable: '+config['loader']) from ex
    if not callable(loader):raise ValueError('deployment model loader is not callable')
    model=loader(config['model'])
    if not callable(getattr(model,'inference',None)):
        raise ValueError('deployment model must expose inference(prompt, image, task=...)')
    def infer(request):
        capability=request['capability']
        task=config.get('task_mapping',{}).get(capability)
        if task is None:raise ValueError('capability has no validated model task mapping')
        image=request.get('observation',{}).get('image_path')
        return model.inference(request['prompt'],image,task=task,do_sample=False)
    return infer