quantum_peer_model.py

import torch
import numpy as np
from quantum_circuit import QuantumCircuit
from quantum_topology import ChernSimonsTopology
from llm_interface import OpenPeerLLMInterface

class QuantumPeerModel:
    def __init__(
        self,
        model_path: str = "OpenPeerAI/OpenPeerLLM",
        checkpoint: str = "bestmodel",
        device: str = None,
        quantum_depth: int = 3
    ):
        if device is None:
            device = "cuda" if torch.cuda.is_available() else "cpu"
            
        self.device = device
        self.topology = ChernSimonsTopology(quantum_depth)
        self.circuit = QuantumCircuit(self.topology)
        self.llm_interface = OpenPeerLLMInterface(model_path, checkpoint, device)
        
    def generate(
        self,
        prompt: str,
        max_length: int = 100,
        quantum_params: dict = None
    ) -> str:
        try:
            # Process input through quantum circuit
            quantum_state = self.circuit.prepare_input(prompt)
            quantum_state = self.circuit.evolve(quantum_state, quantum_params)
            
            # Generate response using quantum-modified state
            response = self.llm_interface.generate(
                prompt,
                quantum_state=quantum_state,
                max_length=max_length
            )
            return response
        except Exception as e:
            print(f"Error in generation: {e}")
            return f"Error: Could not generate response. {str(e)}"