class_docstr: LIT model backed by a remote LIT server.
class_docstr_tok: ["LIT","model","backed","by","a","remote","LIT","server","."]
code: def predict_minibatch(self, inputs: list[JsonDict]) -> list[JsonDict]:
      # Package data as IndexedInput with dummy ids.
      indexed_inputs = [{"id": None, "data": d} for d in inputs]
      logging.info(
          "Querying remote model: /get_preds on %d examples",
          len(indexed_inputs),
      )
      preds = query_lit_server(
          self._url,
          "get_preds",
          params={"model": self._name, "response_simple_json": False},
          inputs=indexed_inputs,
      )
      logging.info(
          "Received %d predictions from remote model.", len(preds)
      )
      return preds
  
file_path: lit/lit_nlp/components/remote_model.py
imports: from typing import Any, Optional
  import urllib
  from absl import logging
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.lib import serialize
  import requests
  import six
label_desc: Use image node_id 5 for calling the RemoteModel obj's underlying member method code with example usage: obj.predict_minibatch(inputs) and returns: preds