Manage flows

Experimental feature

This is an experimental feature, and may change at any time. Learn more.

This documentation will walk you through how to manage your flow with CLI and SDK on Azure AI. The flow examples in this guide come from examples/flows/standard.

In general:

• For CLI, you can run pfazure flow --help in the terminal to see help messages.

• For SDK, you can refer to Promptflow Python Library Reference and check promptflow.azure.PFClient.flows for more flow operations.

Prerequisites

Prerequisites are the same as Quick start.

Let’s take a look at the following topics:

• Manage flows

  • Create a flow

  • List flows

Create a flow

CLI

To set the target workspace, you can either specify it in the CLI command or set default value in the Azure CLI. You can refer to Quick start for more information.

To create a flow to Azure from local flow directory, you can use

# create the flow 
pfazure flow create --flow <path-to-flow-folder> 

# create the flow with metadata
pfazure flow create --flow <path-to-flow-folder> --set display-name=<display-name> description=<description> tags.key1=value1

After the flow is created successfully, you can see the flow summary in the command line.

On Azure portal, you can see the created flow in the flow list.

SDK

1. Import the required libraries

from azure.identity import DefaultAzureCredential, InteractiveBrowserCredential
# azure version promptflow apis
from promptflow.azure import PFClient

2. Get credential

try:
    credential = DefaultAzureCredential()
    # Check if given credential can get token successfully.
    credential.get_token("https://management.azure.com/.default")
except Exception as ex:
    # Fall back to InteractiveBrowserCredential in case DefaultAzureCredential not work
    credential = InteractiveBrowserCredential()

3. Get a handle to the workspace

# Get a handle to workspace
pf = PFClient(
    credential=credential,
    subscription_id="<SUBSCRIPTION_ID>",  # this will look like xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
    resource_group_name="<RESOURCE_GROUP>",
    workspace_name="<AML_WORKSPACE_NAME>",
)

4. Create the flow

# specify flow path
flow = "./web-classification"

# create flow to Azure
flow = pf.flows.create_or_update(
    flow=flow,  # path to the flow folder
    display_name="my-web-classification",  # it will be "web-classification-{timestamp}" if not specified
    type="standard",  # it will be "standard" if not specified
)

List flows

CLI

List flows with default json format:

pfazure flow list --max-results 1

SDK

# reuse the pf client created in "create a flow" section
flows = pf.flows.list(max_results=1)