Port code to Qiskit Serverless

from qiskit.transpiler.preset_passmanagers import generate_preset_pass_manager
from qiskit_ibm_runtime import QiskitRuntimeService
from qiskit.circuit.random import random_circuit
 
qc_random = [(random_circuit(20, 20, measure=True)) for _ in range(30)]
optimization_level = 3
 
# If you have not previously saved your credentials, follow instructions at
# https://quantum.cloud.ibm.com/docs/guides/cloud-setup
# to authenticate with your API token.
service = QiskitRuntimeService(channel="ibm_cloud")
backend = service.get_backend(backend_name)
 
pass_manager = generate_preset_pass_manager(
    optimization_level=optimization_level, backend=backend
)
 
# @distribute_task(target={"cpu": 1})
def transpile_parallel(circuit, pass_manager):
    """Distributed transpilation for an abstract circuit into an ISA circuit for a given backend."""
    
    isa_circuit = pass_manager.run(circuit)
 
    return isa_circuit
 
transpiled_circuits = [
    transpile_parallel(circuit, pass_manager)
    for circuit in circuits
]
 
print(transpiled_circuits)

# transpile_remote.py
 
from qiskit.transpiler.preset_passmanagers import generate_preset_pass_manager
from qiskit_serverless import get_arguments, save_result, distribute_task, get
from qiskit_ibm_runtime import QiskitRuntimeService
 
# Get program arguments
arguments = get_arguments()
circuits = arguments.get("circuits")
backend_name = arguments.get("backend_name")
optimization_level = arguments.get("optimization_level")
pass_manager = generate_preset_pass_manager(
optimization_level=optimization_level, backend=backend_name
)
 
# Distribute task across workers
@distribute_task(target={"cpu": 1})
def transpile_parallel(circuit, pass_manager):
"""Distributed transpilation for an abstract circuit into an ISA circuit for a given backend."""
 
isa_circuit = pass_manager.run(circuit)
 
return isa_circuit
 
try:
# Get backend
# Follow instructions at https://quantum.cloud.ibm.com/docs/guides/cloud-setup to authenticate with your API token.
service = QiskitRuntimeService(channel="ibm_cloud")
backend = service.get_backend(backend_name)
 
# run distributed tasks as async function
# we get task references as a return type
sample_task_references = [
    transpile_parallel(circuit, pass_manager)
    for circuit in circuits
]
 
# now we need to collect results from task references
results = get(sample_task_references)
 
# Return results
save_result({
    "transpiled_circuits": results
})
 
except Exception as e:
# Exception handling 
import traceback
print(traceback.format_exc())