evo_plugin.py

# evo_plugin.py — YOUR Evo integration (replace example with your code)
import torch

class EvoTextGenerator:
    def __init__(self, weights_path: str = "models/evo_decoder.pt"):
        # TODO: load your Evo tokenizer + model here
        # self.tok = YourEvoTokenizer.load(...)
        # self.model = YourEvoModel.load_state_dict(torch.load(weights_path, map_location="cpu"))
        # self.model.eval()
        pass

    @torch.no_grad()
    def generate(self, prompt: str, max_new_tokens: int = 200, temperature: float = 0.4) -> str:
        # TODO: tokenize -> generate -> detokenize
        # ids = self.tok.encode(prompt)
        # out = self.model.generate(ids, max_new_tokens=max_new_tokens, temperature=temperature)
        # return self.tok.decode(out)
        return "TODO: return Evo-generated text"

def load_model():
    return EvoTextGenerator()