import torch, torch.nn as nn
from huggingface_hub import hf_hub_download
from safetensors.torch import load_file

class OpenAI:
    def __init__(self, token=None):
        self.d = "cuda" if torch.cuda.is_available() else "cpu"
        class M(nn.Module):
            def __init__(self): 
                super().__init__(); self.embedding = nn.Embedding(256, 1); self.classifier = nn.Linear(1, 2, bias=False)
            def forward(self, x): return self.classifier(self.embedding(x).float().mean(0))
        self.m = M().to(self.d); self.m.load_state_dict(load_file(hf_hub_download("faunix/YEN", "model.safetensors", token=token)))
        self.chat = type('o', (object,), {"completions": type('o', (object,), {"create": self._c})()})()
    def _c(self, **k):
        t = torch.tensor([ord(c)%256 for c in k['messages'][-1]['content']], device=self.d)
        with torch.no_grad(): out = self.m(t); res = "Yes" if out[1] > out[0] else "No"
        return type('o', (object,), {"choices": [type('o', (object,), {"message": type('o', (object,), {"content": res})()})()]})()