kaldesai commented on code in PR #600:
URL:
https://github.com/apache/incubator-kie-kogito-docs/pull/600#discussion_r1531863318
##########
serverlessworkflow/modules/ROOT/pages/use-cases/advanced-developer-use-cases/integrations/custom-functions-python.adoc:
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@@ -0,0 +1,115 @@
+= Invoking Python from {product_name}
+:compat-mode!:
+// Metadata:
+:description: Describe Python execution capabilities
+:keywords: kogito, workflow, quarkus, serverless, python, AI
+
+This document describes how to integrate python scripts and functions into
your workflow using {product_name} custom functions. The code appearing in this
document is copied from
link:{kogito_sw_examples_url}/serverless-workflow-python-quarkus[`serverless-workflow-python-quarkus`]
example application and
link:{kogito_runtimes_url}/quarkus/addons/python/integration-tests/src/main/resources/PythonService.sw.json[PythonService]
integration test.
+
+== Enable Python support
+
+ To enable Python support, you need to the python add-on dependency to your
{prouct_name} module `pom.xml` file
+
+[source,xml]
+----
+<dependency>
+ <groupId>org.apache.kie.sonataflow</groupId>
+ <artifactId>sonataflow-addons-quarkus-python</artifactId>
+</dependency>
+----
+
+== Invoking embedded Python script.
+
+{product_name} supports of execution python script in the same memory address
than the running workflow.
+
+To invoke a python script the first step is to define a custom python function
at the beginning of the flow.
+
+[source,json]
+----
+ "functions": [
+ {
+ "name": "python",
+ "type": "custom",
+ "operation": "script:python"
+ }
+ ]
+----
+
+Once done, you can use that function several times to execute arbitrary python
code. The python code is provided as argument of the function call through
`script` property.
+
+[source,json]
+----
+"functionRef":
+ "refName": "python",
+ "arguments": {
+ "script": "import numpy as np"
+ }
+ }
+----
+
+Previous snippet imports link:https://numpy.org/[numpy] library. The same
python function can be invoked again to generate an array containing three
random numbers between 0 and 10.
+
+[source,json]
+----
+"functionRef": {
+ "refName": "python",
+ "arguments": {
+ "script": "rng = np.random.default_rng().integers(low=0,high=10,size=3)"
+ }
+ }
+----
+
+To access the result of the embedded python invocation, {product_name}
provides an special context variable: `$WORKFLOW.python`. Therefore, if you
want to set `rng` variable from previous script as `output` property of the
workflow model, you write
Review Comment:
```suggestion
To access the result of the embedded python invocation, {product_name}
provides a special context variable: `$WORKFLOW.python`. Therefore, if you want
to set the `rng` variable from the previous script as the `output` property of
the workflow model, you write
```
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