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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)}" |