import grpc
import numpy as np
from typing import Optional

# These would be generated from the .proto file
from . import node_service_pb2
from . import node_service_pb2_grpc

from ..peer_handle import PeerHandle
from inference.shard import Shard

class GRPCPeerHandle(PeerHandle):
    def __init__(self, id: str, address: str):
        self._id = id
        self.address = address

    def id(self) -> str:
        return self._id

    async def connect(self):
        self.channel = grpc.aio.insecure_channel(self.address)
        self.stub = node_service_pb2_grpc.NodeServiceStub(self.channel)

    async def disconnect(self):
        await self.channel.close()

    async def send_prompt(self, shard: Shard, prompt: str) -> Optional[np.array]:
        request = node_service_pb2.PromptRequest(prompt=prompt, shard=node_service_pb2.Shard(model_id=shard.model_id, start_layer=shard.start_layer, end_layer=shard.end_layer, n_layers=shard.n_layers))
        response = await self.stub.SendPrompt(request)
        print(f"Sent prompt to {self.address}: {prompt}")

        if not response.tensor_data or not response.shape or not response.dtype:
            return None

        return np.frombuffer(response.tensor_data, dtype=np.dtype(response.dtype)).reshape(response.shape)

    async def send_tensor(self, shard: Shard, tensor: np.ndarray, target: Optional[str] = None) -> Optional[np.array]:
        request = node_service_pb2.TensorRequest(
            shard=node_service_pb2.Shard(model_id=shard.model_id, start_layer=shard.start_layer, end_layer=shard.end_layer, n_layers=shard.n_layers),
            tensor = node_service_pb2.Tensor(
                tensor_data=tensor.tobytes(),
                shape=tensor.shape,
                dtype=str(tensor.dtype)
            ),
            target=target
        )
        response = await self.stub.SendTensor(request)
        if target:
            print(f"Sent tensor to {self.address} with target {target}: shape {tensor.shape}")
        else:
            print(f"Sent tensor to {self.address}: shape {tensor.shape}")

        if not response.tensor_data or not response.shape or not response.dtype:
            return None

        return np.frombuffer(response.tensor_data, dtype=np.dtype(response.dtype)).reshape(response.shape)

    async def reset_shard(self, shard: Shard) -> None:
        request = node_service_pb2.ResetShardRequest(shard=node_service_pb2.Shard(model_id=shard.model_id, start_layer=shard.start_layer, end_layer=shard.end_layer, n_layers=shard.n_layers))
        await self.stub.ResetShard(request)
        print(f"Reset shard {shard} on {self.address}")