# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved. # SPDX-License-Identifier: Apache-2.0 # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from dataclasses import dataclass from io import BytesIO from typing import Any, Callable, Dict import torch import zmq class TorchSerializer: @staticmethod def to_bytes(data: dict) -> bytes: buffer = BytesIO() torch.save(data, buffer) return buffer.getvalue() @staticmethod def from_bytes(data: bytes) -> dict: buffer = BytesIO(data) obj = torch.load(buffer, weights_only=False) return obj @dataclass class EndpointHandler: handler: Callable requires_input: bool = True class BaseInferenceServer: """ An inference server that spin up a ZeroMQ socket and listen for incoming requests. Can add custom endpoints by calling `register_endpoint`. """ def __init__(self, host: str = "*", port: int = 5555): self.running = True self.context = zmq.Context() self.socket = self.context.socket(zmq.REP) self.socket.bind(f"tcp://{host}:{port}") self._endpoints: dict[str, EndpointHandler] = {} # Register the ping endpoint by default self.register_endpoint("ping", self._handle_ping, requires_input=False) self.register_endpoint("kill", self._kill_server, requires_input=False) def _kill_server(self): """ Kill the server. """ self.running = False def _handle_ping(self) -> dict: """ Simple ping handler that returns a success message. """ return {"status": "ok", "message": "Server is running"} def register_endpoint(self, name: str, handler: Callable, requires_input: bool = True): """ Register a new endpoint to the server. Args: name: The name of the endpoint. handler: The handler function that will be called when the endpoint is hit. requires_input: Whether the handler requires input data. """ self._endpoints[name] = EndpointHandler(handler, requires_input) def run(self): addr = self.socket.getsockopt_string(zmq.LAST_ENDPOINT) print(f"Server is ready and listening on {addr}") while self.running: try: message = self.socket.recv() request = TorchSerializer.from_bytes(message) endpoint = request.get("endpoint", "get_action") if endpoint not in self._endpoints: raise ValueError(f"Unknown endpoint: {endpoint}") handler = self._endpoints[endpoint] result = ( handler.handler(request.get("data", {})) if handler.requires_input else handler.handler() ) self.socket.send(TorchSerializer.to_bytes(result)) except Exception as e: print(f"Error in server: {e}") import traceback print(traceback.format_exc()) self.socket.send(b"ERROR") class BaseInferenceClient: def __init__(self, host: str = "localhost", port: int = 5555, timeout_ms: int = 15000): self.context = zmq.Context() self.host = host self.port = port self.timeout_ms = timeout_ms self._init_socket() def _init_socket(self): """Initialize or reinitialize the socket with current settings""" self.socket = self.context.socket(zmq.REQ) self.socket.connect(f"tcp://{self.host}:{self.port}") def ping(self) -> bool: try: self.call_endpoint("ping", requires_input=False) return True except zmq.error.ZMQError: self._init_socket() # Recreate socket for next attempt return False def kill_server(self): """ Kill the server. """ self.call_endpoint("kill", requires_input=False) def call_endpoint( self, endpoint: str, data: dict | None = None, requires_input: bool = True ) -> dict: """ Call an endpoint on the server. Args: endpoint: The name of the endpoint. data: The input data for the endpoint. requires_input: Whether the endpoint requires input data. """ request: dict = {"endpoint": endpoint} if requires_input: request["data"] = data self.socket.send(TorchSerializer.to_bytes(request)) message = self.socket.recv() if message == b"ERROR": raise RuntimeError("Server error") return TorchSerializer.from_bytes(message) def __del__(self): """Cleanup resources on destruction""" self.socket.close() self.context.term() class ExternalRobotInferenceClient(BaseInferenceClient): """ Client for communicating with the RealRobotServer """ def set_observation(self, observation: dict[str, Any]): self.call_endpoint("set_observation", data=observation) def get_action(self, time: float | None = None) -> Dict[str, Any]: """ Get the action from the server. The exact definition of the observations is defined by the policy, which contains the modalities configuration. """ return self.call_endpoint("get_action", data={"time": time}) def get_modality_config(self) -> dict[str, Any]: return self.call_endpoint("get_modality_config")