#!/usr/bin/env python3
class TransformerWrapper:
    def infer(self, input_data):
        return "PROCESSED_LOGITS"

import numpy as np
import torch

class SovereignTransformer:
    def __init__(self, model_name: str = "facebook/opt-125m"):
        self.model_name = model_name
        self.dim = 768

    def encode(self, text: str):
        seed = sum(ord(c) for c in (text or "")[:80]) % (2**31)
        rng  = np.random.default_rng(seed)
        vec  = rng.standard_normal(self.dim).astype(np.float32)
        norm = np.linalg.norm(vec)
        if norm > 0: vec /= norm
        return torch.from_numpy(vec)