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136 lines
3.8 KiB
Markdown
136 lines
3.8 KiB
Markdown
# Manage flows
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This documentation will walk you through how to manage your flow with CLI and SDK on [Azure AI](https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/overview-what-is-prompt-flow?view=azureml-api-2).
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The flow examples in this guide come from [examples/flows/standard](https://github.com/microsoft/promptflow/tree/main/examples/flows/standard).
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In general:
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- For `CLI`, you can run `pfazure flow --help` in the terminal to see help messages.
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- For `SDK`, you can refer to [Promptflow Python Library Reference](../../reference/python-library-reference/promptflow-azure/promptflow.rst) and check `promptflow.azure.PFClient.flows` for more flow operations.
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:::{admonition} Prerequisites
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- Refer to the prerequisites in [Quick start](./run-promptflow-in-azure-ai.md#prerequisites).
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- Use the `az login` command in the command line to log in. This enables promptflow to access your credentials.
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:::
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Let's take a look at the following topics:
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- [Manage flows](#manage-flows)
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- [Create a flow](#create-a-flow)
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- [List flows](#list-flows)
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## Create a flow
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::::{tab-set}
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:::{tab-item} CLI
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:sync: CLI
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To set the target workspace, you can either specify it in the CLI command or set default value in the Azure CLI.
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You can refer to [Quick start](./run-promptflow-in-azure-ai.md#submit-a-run-to-workspace) for more information.
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To create a flow to Azure from local flow directory, you can use
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```bash
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# create the flow
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pfazure flow create --flow <path-to-flow-folder>
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# create the flow with metadata
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pfazure flow create --flow <path-to-flow-folder> --set display_name=<display-name> description=<description> tags.key1=value1
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```
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After the flow is created successfully, you can see the flow summary in the command line.
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:::
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:::{tab-item} SDK
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:sync: SDK
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1. Import the required libraries
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```python
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from azure.identity import DefaultAzureCredential, InteractiveBrowserCredential
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# azure version promptflow apis
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from promptflow.azure import PFClient
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```
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2. Get credential
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```python
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try:
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credential = DefaultAzureCredential()
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# Check if given credential can get token successfully.
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credential.get_token("https://management.azure.com/.default")
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except Exception as ex:
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# Fall back to InteractiveBrowserCredential in case DefaultAzureCredential not work
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credential = InteractiveBrowserCredential()
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```
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3. Get a handle to the workspace
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```python
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# Get a handle to workspace
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pf = PFClient(
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credential=credential,
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subscription_id="<SUBSCRIPTION_ID>", # this will look like xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
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resource_group_name="<RESOURCE_GROUP>",
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workspace_name="<AML_WORKSPACE_NAME>",
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)
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```
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4. Create the flow
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```python
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# specify flow path
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flow = "./web-classification"
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# create flow to Azure
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flow = pf.flows.create_or_update(
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flow=flow, # path to the flow folder
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display_name="my-web-classification", # it will be "web-classification-{timestamp}" if not specified
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type="standard", # it will be "standard" if not specified
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)
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```
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:::
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::::
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On Azure portal, you can see the created flow in the flow list.
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And the flow source folder on file share is `Users/<alias>/promptflow/<flow-display-name>`:
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Note that if the flow display name is not specified, it will default to the flow folder name + timestamp. (e.g. `web-classification-11-13-2023-14-19-10`)
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## List flows
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::::{tab-set}
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:::{tab-item} CLI
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:sync: CLI
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List flows with default json format:
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```bash
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pfazure flow list --max-results 1
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```
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:::
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:::{tab-item} SDK
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:sync: SDK
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```python
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# reuse the pf client created in "create a flow" section
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flows = pf.flows.list(max_results=1)
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```
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:::
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:::: |