update plugin references from DI v25.2.2-305-g2e9513c76

Author: seebi

data/plugins.json

@@ -49,11 +49,12 @@ nav:
     - "Set or Overwrite parameters": cmem_plugin_parameters-ParametersPlugin.md
     - "SHACL validation with pySHACL": shacl-pyshacl.md
     - "SOQL query (Salesforce)": cmem_plugin_salesforce-SoqlQuery.md
+    - "Spark SQL query": CustomSQLExecution.md
     - "SPARQL Construct query": sparqlCopyOperator.md
     - "SPARQL Select query": sparqlSelectOperator.md
     - "SPARQL Update query": sparqlUpdateOperator.md
     - "Split file": cmem_plugin_splitfile-plugin_splitfile-SplitFilePlugin.md
-    - "SQL query": CustomSQLExecution.md
+    - "SQL Update query": sqlUpdateQueryOperator.md
     - "Start Workflow per Entity": cmem_plugin_loopwf-task-StartWorkflow.md
     - "Store Vector Embeddings": cmem_plugin_pgvector-Store.md
     - "Unpivot": Unpivot.md

docs/build/reference/customtask/.pages

@@ -1,16 +1,16 @@
 ---
-title: "SQL query"
-description: "Executes a custom SQL query on the first input dataset and returns the result as its output."
+title: "Spark SQL query"
+description: "Executes a custom SQL query on the first input Spark dataframe and returns the result as its output."
 icon: octicons/cross-reference-24
 tags: 
     - WorkflowTask
 ---
-# SQL query
+# Spark SQL query
 <!-- This file was generated - DO NOT CHANGE IT MANUALLY -->
 
 
 
-Executes a custom SQL query on the first input dataset and returns the result as its output.
+Executes a custom SQL query on the first input Spark dataframe and returns the result as its output.
 
 
 ## Parameter

docs/build/reference/customtask/CustomSQLExecution.md

@@ -75,6 +75,16 @@ Pods are an abstraction that represent groups of one or more application contain
 
 
 
+### Container
+
+In case there is more than one container in the pod OR the default container selection does not work, you need to specify the container ID in addition to the pod ID.
+
+- ID: `container`
+- Datatype: `string`
+- Default Value: `None`
+
+
+
 ### Command
 
 The command to execute.

docs/build/reference/customtask/cmem_plugin_kubernetes-Execute.md

@@ -16,28 +16,17 @@ tags:
     e.g. with cmemc.
 
 
-This plugin creates vector embeddings from text data using OpenAI's embeddings API.
+This plugin creates vector embeddings from text data using an OpenAI compatible embeddings API.
 It processes input entities containing text data and generates high-dimensional vector
 representations that capture semantic meaning.
 
 ## Features
 
-- Supports OpenAI embeddings models (e.g., text-embedding-3-small)
+- Supports OpenAI embeddings models (e.g., `text-embedding-3-small`)
 - Batch processing for efficient API usage
 - Configurable input/output paths
-- Automatic schema generation based on configuration
 - Built-in error handling and workflow cancellation support
 
-## Configuration
-
-- **URL**: OpenAI API endpoint (default: https://api.openai.com/v1)
-- **API Key**: Your OpenAI API key for authentication
-- **Model**: The embedding model to use (e.g., text-embedding-3-small)
-- **Timeout**: Request timeout in milliseconds (default: 10000)
-- **Buffer Size**: Number of texts to process per batch (default: 100)
-- **Input Paths**: Comma-separated list of entity paths to embed (default: "text")
-- **Output Paths**: Configurable paths for embedding vectors and source text
-
 ## Input/Output
 
 - **Input**: Entities with text data in specified paths
@@ -56,27 +45,37 @@ representations that capture semantic meaning.
 
 ### Base URL
 
-URL of the OpenAI API (without endpoint path and without trailing slash)
+The base URL of the OpenAI compatible API (without endpoint path).
 
 - ID: `base_url`
 - Datatype: `string`
-- Default Value: `https://api.openai.com/v1`
+- Default Value: `https://api.openai.com/v1/`
+
+
+
+### API Type
+
+Select the API client type. This determines the authentication method and endpoint configuration used for API requests. Choose `OPENAI` for direct OpenAI API access or `AZURE_OPENAI` for Azure-hosted OpenAI services. Consider using the API version advanced parameter in case you access Azure-hosted OpenAI services.
+
+- ID: `api_type`
+- Datatype: `enumeration`
+- Default Value: `OPENAI`
 
 
 
-### The OpenAI API key
+### API key
 
-Fill the OpenAI API key if needed (or give a dummy value in case you access an unsecured endpoint).
+An optional API key for authentication.
 
 - ID: `api_key`
 - Datatype: `password`
 - Default Value: `None`
 
 
 
-### The embeddings model, e.g. text-embedding-3-small
+### Embeddings model
 
-The embeddings model to use (e.g., text-embedding-3-small).
+The identifier of the embeddings model to use. Available model IDs for some public providers can be found here: [Claude](https://docs.claude.com/en/docs/build-with-claude/embeddings#available-models), [OpenAI](https://platform.openai.com/docs/guides/embeddings#embedding-models).
 
 - ID: `model`
 - Datatype: `string`
@@ -108,9 +107,19 @@ Paths from input entities to forward to output without modification. These paths
 
 ## Advanced Parameter
 
-### Timeout (Single Request, in Milliseconds)
+### API Version
+
+Azure OpenAI API version (only used when API Type is `AZURE_OPENAI`). For more information about OpenAI API version at Azure, please see [the documentation](https://learn.microsoft.com/en-gb/azure/ai-foundry/openai/api-version-lifecycle).
+
+- ID: `api_version`
+- Datatype: `string`
+- Default Value: `None`
+
+
 
+### Timeout (milliseconds)
 
+The timeout for a single API request in milliseconds.
 
 - ID: `timout_single_request`
 - Datatype: `Long`