Command Line Interface

Learn how to use the PySDK command line interface to manage AI models, control your AI server, and streamline model downloads.

As a part of PySDK installation, the degirum executable console script is installed into the system path. It implements command-line interface (CLI) to various PySDK management facilities. This console script extends PySDK functionality through the mechanism of entry points.

The PySDK CLI supports the following commands:

Command	Description
download-zoo	Download AI models from the cloud model zoo
server	Control operation of the AI server
sys-info	Get system information dump
trace	Command to manage AI server tracing facility
version	Print PySDK version

You invoke the console script passing the command from the table above as its first argument followed by command-specific parameters described in the following sections.

degirum <command> <arguments>

Download Model Zoo

Command: download-zoo

Using this command you can download ML models from the cloud model zoo of your choice specified by URL. The command has the following parameters:

Parameter	Description	Possible Values	Default
--path	Local filesystem path to store models downloaded from a model zoo repo	Valid local directory path	Current directory
--url	Cloud model zoo URL	"https://cs.degirum.com[/<zoo URL>]"	"https://cs.degirum.com"
--token	Cloud API access token	Valid token obtained at cs.degirum.com	Empty
--model_family	Model family name filter: model name substring or regular expression	Any	Empty
--device	Target inference device filter	ORCA, CPU, GPU, EDGETPU, MYRIAD, DLA, DLA_FALLBACK, NPU, RK3588, RK3566, RK3568, NXP_VX, NXP_ETHOSU, ARMNN, VITIS_NPU	Empty
--runtime	Runtime agent type filter	N2X, TFLITE, TENSORRT, OPENVINO, ONNX, RKNN	Empty
--precision	Model calculation precision filter	QUANT, FLOAT	None
--pruned	Model density filter	PRUNED, DENSE	None

The URL parameter is specified in the "https://cs.degirum.com/<zoo URL>" format. Here <zoo URL> suffix is the name of the cloud model zoo in the form of <organization>/<zoo>. You can obtain the model zoo URL suffix on DeGirum Cloud Portal site https://cs.degirum.com under Management | Models main menu item: just select the model zoo you want to access to open the model zoo page and click copy button near the model zoo name to copy the model zoo URL suffix into the clipboard.

Filter parameters work the same way as in degirum.zoo_manager.ZooManager.list_models method: they allow you downloading only models satisfying filter conditions.

Once models are downloaded into the directory specified by --path parameter, you may use this directory as the model zoo to be served by AI server (see Server Control Command section).

Example.

Download models for ORCA device type from DeGirum Public cloud model zoo into ./my-zoo directory.

degirum download-zoo --path ./my-zoo --token <your cloud API access token> --device ORCA

Here <your cloud API access token> is your cloud API access token, which you can generate on DeGirum Cloud Portal site https://cs.degirum.com under Management | My Tokens main menu item.

Server Control

server

Using this command you can start AI server, shut it down, or request AI server to rescan its local model zoo.

You can control only AI server which runs on the same host where you execute this command. The control of remote AI servers is disabled for security reasons.

This command has the following subcommands, which are passed just after the command:

Sub-command	Description
start	Start AI server
rescan-zoo	Request AI server to rescan its model zoo
shutdown	Request AI server to shutdown
cache-dump	Dump AI server inference agent cache info

The command has the following parameters:

Parameter	Applicable To	Description	Possible Values	Default
--zoo	start	Local model zoo directory to serve models from (applicable only to start subcommand)	Any valid path	Current directory
--quiet	start	Do not display any output (applicable only to start subcommand)	N/A	Disabled
--port	start	TCP port to bind AI server to	1...65535	8778
--protocol	start	AI server protocol to use	asio, http, both	asio

Starting from PySDK version 0.10.0, AI server supports two protocols: asio and http. The asio protocol is DeGirum custom socket-based AI server protocol, supported by all previous PySDK versions. The http protocol is a new protocol, which is based on REST HTTP requests and WebSockets streaming. The http protocol allows to use AI server from any programming language, which supports HTTP requests and WebSockets, such as browser-based JavaScript, which does not support native sockets, thus precluding the use of asio protocol.

The asio protocol is selected by default. You can select the http protocol by specifying --protocol http. You may select both protocols by specifying --protocol both. In this case, AI server will listen to both protocols on two consecutive TCP ports: the first port is used for asio protocol, the second port is used for http protocol.

Examples.

Start AI server to serve models from ./my-zoo directory, bind it to default port, and use asio protocol:

degirum server start --zoo ./my-zoo

Start AI server to serve models from ./my-zoo directory, use asio protocol on port 12345, and use http protocol on port 12346:

degirum server start --zoo ./my-zoo --port 12345 --protocol both

System Info

Command: sys-info

Using this command you can query the system information either for the local system or for the remote AI server host. The system info dump is printed to the console.

The command has the following parameters:

Parameter	Description	Possible Values	Default
--host	Remote AI server hostname or IP address; omit to query local system	Valid hostname, IP address, or empty	Empty

Example.

Query system info from remote AI server at IP address 192.168.0.101:

degirum sys-info --host 192.168.0.101

Manage Tracing

Command: trace

Using this command you can manage AI server tracing facility.

AI server tracing facility is used for AI server debugging and time profiling. It is designed mostly for DeGirum customer support and not intended to be used by the end user directly.

This command has the following subcommands, which are passed just after the command:

Sub-command	Description
list	List all available trace groups
configure	Configure trace levels for trace groups
read	Read trace data to file

The command has the following parameters:

Parameter	Applicable To	Description	Possible Values	Default
--host	All subcommands	Remote AI server hostname or IP address	Valid hostname or IP address	localhost
--file	read	Filename to save trace data into; omit to print to console	Valid local filename	Empty
--filesize	read	Maximum trace data size to read	Any integer number	10000000
--basic	configure	Set Basic trace level for a given list of trace groups	One or multiple trace group names as returned by list sub-command	Empty
--detailed	configure	Set Detailed trace level for a given list of trace groups	One or multiple trace group names as returned by list sub-command	Empty
--full	configure	Set Full trace level for a given list of trace groups	One or multiple trace group names as returned by list sub-command	Empty

Examples.

Query AI server at 192.168.0.101 address for the list of available trace groups and print it to console:

degirum trace list --host 192.168.0.101

Configure tracing for AI server on localhost: by setting various tracing levels for various trace groups:

degirum trace configure --basic CoreTaskServer --detailed OrcaDMA OrcaRPC --full CoreRuntime

Read trace data from AI server on localhost and save it to a file ./my-trace-1.txt

degirum trace read --file ./my-trace-1.txt