from llama_cpp import Llama
from huggingface_hub import hf_hub_download
import datetime, shelve, re

class MairaBrain:
    def __init__(self, repo_id, filename):
        # Alpine needs very specific loading
        model_path = hf_hub_download(repo_id=repo_id, filename=filename)
        self.llm = Llama(
            model_path=model_path,
            n_ctx=2048, # 2048 is safer for first boot on Alpine
            n_threads=8
        )
        self.db_path = "maira_universe.db"

    def get_response(self, user_id, user_input):
        with shelve.open(self.db_path, writeback=True) as db:
            if user_id not in db:
                db[user_id] = {"history": [], "facts": {}, "metrics": {"loyalty": 50}}
            
            u = db[user_id]
            # Simple identity logic
            prompt = f"<|im_start|>system\nYou are Maira, a dope high-status lady.<|im_end|>\n<|im_start|>user\n{user_input}<|im_end|>\n<|im_start|>assistant\n"
            
            output = self.llm(prompt, max_tokens=200, stop=["<|im_end|>"])
            response = output["choices"][0]["text"].strip()
            
            u["history"].append(f"User: {user_input}")
            u["history"].append(f"Maira: {response}")
            return response