TorchServe Python Client
Install
pip install torchserve_clientUsage
Using torchserve_client is a breeze! It has support for both REST APIs
and gRPC APIs.
REST Client
To make calls to REST endpoint, simply initialize a
TorchServeClientREST
object as shown below:
from torchserve_client import TorchServeClientREST
# Initialize the REST TorchServeClient object
ts_client = TorchServeClientREST()
ts_clientTorchServeClient(base_url=http://localhost, management_port=8081, inference_port=8080)
If you wish to customize the base URL, management port, or inference port of your TorchServe server, you can pass them as arguments during initialization:
from torchserve_client import TorchServeClientREST
# Customize the base URL, management port, and inference port
ts_client = TorchServeClientREST(base_url='http://your-torchserve-server.com',
management_port=8081, inference_port=8080)
ts_clientTorchServeClient(base_url=http://your-torchserve-server.com, management_port=8081, inference_port=8080)
gRPC Client
To create a gRPC client, simply create a
TorchServeClientGRPC
object
from torchserve_client import TorchServeClientGRPC
# Initialize the gRPC TorchServeClient object
ts_client = TorchServeClientGRPC()
ts_clientTorchServeClientGRPC(base_url=localhost, management_port=7071, inference_port=7070)
To customize base URL and default ports, pass them as arguments during initialization
from torchserve_client import TorchServeClientGRPC
# Initialize the gRPC TorchServeClient object
ts_client = TorchServeClientGRPC(base_url='http://your-torchserve-server.com',
management_port=7071, inference_port=7070)
ts_clientTorchServeClientGRPC(base_url=your-torchserve-server.com, management_port=7071, inference_port=7070)
With these intuitive APIs at your disposal, you can harness the full
power of the Management and Inference API and take your application to
next level. Happy inferencing!
