chore: import upstream snapshot with attribution

2026-07-13 13:39:52 +08:00
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+# Basic standard flow
+A basic standard flow using custom python tool that calls Azure OpenAI with connection info stored in environment variables.
+
+Tools used in this flow：
+- `prompt` tool
+- custom `python` Tool
+
+Connections used in this flow:
+- None
+
+## Prerequisites
+
+Install promptflow sdk and other dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+## Run flow
+
+- Prepare your Azure OpenAI resource follow this [instruction](https://learn.microsoft.com/en-us/azure/cognitive-services/openai/how-to/create-resource?pivots=web-portal) and get your `api_key` if you don't have one.
+
+- Setup environment variables
+
+Ensure you have put your azure OpenAI endpoint key in [.env](.env) file. You can create one refer to this [example file](.env.example).
+
+```bash
+cat .env
+```
+
+- Test flow/node
+```bash
+# test with default input value in flow.dag.yaml
+pf flow test --flow .
+
+# test with flow inputs
+pf flow test --flow . --inputs text="Java Hello World!"
+
+# test node with inputs
+pf flow test --flow . --node llm --inputs prompt="Write a simple Hello World program that displays the greeting message."
+```
+
+- Create run with multiple lines data
+```bash
+# using environment from .env file (loaded in user code: hello.py)
+pf run create --flow . --data ./data.jsonl --column-mapping text='${data.text}' --stream
+```
+
+You can also skip providing `column-mapping` if provided data has same column name as the flow.
+Reference [here](https://aka.ms/pf/column-mapping) for default behavior when `column-mapping` not provided in CLI.
+
+- List and show run meta
+```bash
+# list created run
+pf run list
+
+# get a sample run name
+name=$(pf run list -r 10 | jq '.[] | select(.name | contains("basic_variant_0")) | .name'| head -n 1 | tr -d '"')
+
+# show specific run detail
+pf run show --name $name
+
+# show output
+pf run show-details --name $name
+
+# visualize run in browser
+pf run visualize --name $name
+```
+
+## Run flow with connection
+Storing connection info in .env with plaintext is not safe. We recommend to use `pf connection` to guard secrets like `api_key` from leak.
+
+- Show or create `open_ai_connection`
+```bash
+# create connection from `azure_openai.yml` file
+# Override keys with --set to avoid yaml file changes
+pf connection create --file ../../../connections/azure_openai.yml --set api_key=<your_api_key> api_base=<your_api_base>
+
+# check if connection exists
+pf connection show -n open_ai_connection
+```
+
+- Test using connection secret specified in environment variables
+**Note**: we used `'` to wrap value since it supports raw value without escape in powershell & bash. For windows command prompt, you may remove the `'` to avoid it become part of the value.
+
+```bash
+# test with default input value in flow.dag.yaml
+pf flow test --flow . --environment-variables AZURE_OPENAI_API_KEY='${open_ai_connection.api_key}' AZURE_OPENAI_API_BASE='${open_ai_connection.api_base}'
+```
+
+- Create run using connection secret binding specified in environment variables, see [run.yml](run.yml)
+```bash
+# create run
+pf run create --flow . --data ./data.jsonl --stream --environment-variables AZURE_OPENAI_API_KEY='${open_ai_connection.api_key}' AZURE_OPENAI_API_BASE='${open_ai_connection.api_base}' --column-mapping text='${data.text}'
+# create run using yaml file
+pf run create --file run.yml --stream
+
+# show outputs
+name=$(pf run list -r 10 | jq '.[] | select(.name | contains("basic_variant_0")) | .name'| head -n 1 | tr -d '"')
+pf run show-details --name $name
+```
+
+## Run flow in cloud with connection
+- Assume we already have a connection named `open_ai_connection` in workspace.
+```bash
+# set default workspace
+az account set -s <your_subscription_id>
+az configure --defaults group=<your_resource_group_name> workspace=<your_workspace_name>
+```
+
+- Create run
+```bash
+# run with environment variable reference connection in azureml workspace
+pfazure run create --flow . --data ./data.jsonl --environment-variables AZURE_OPENAI_API_KEY='${open_ai_connection.api_key}' AZURE_OPENAI_API_BASE='${open_ai_connection.api_base}' --column-mapping text='${data.text}' --stream
+# run using yaml file
+pfazure run create --file run.yml --stream
+```
+
+- List and show run meta
+```bash
+# list created run
+pfazure run list -r 3
+
+# get a sample run name
+name=$(pfazure run list -r 100 | jq '.[] | select(.name | contains("basic_variant_0")) | .name'| head -n 1 | tr -d '"')
+
+# show specific run detail
+pfazure run show --name $name
+
+# show output
+pfazure run show-details --name $name
+
+# visualize run in browser
+pfazure run visualize --name $name
+```