keyVaultUri keyVaultKeyName parameters mismatch between SearchResourceEncryptionKey and SearchIndexerSkillset results request is invalid when creating skillset in azure-search-documents SDK (v11.6.0b5)

[YVass1]

• Package Name: azure.search.documents
• Package Version: 11.6.0b5
• Operating System: OSX, version: 14.6.1
• Python Version: 3.11.10

Describe the bug
While creating a skillset for indexer for Azure AI Search, I encounter an error indicating missing parameters for the encryption key:

--- Logging error ---
  File "/Users/<redacted-project-path>/.venv/lib/python3.11/site-packages/azure/search/documents/indexes/_generated/aio/operations/_skillsets_operations.py", line 261, in create_or_update
    raise HttpResponseError(response=response, model=error)
azure.core.exceptions.HttpResponseError: () The request is invalid. Details: encryptionKey.keyVaultUri : The keyVaultUri field is required.
encryptionKey.keyVaultKeyName : The keyVaultKeyName field is required.
Code: 
Message: The request is invalid. Details: encryptionKey.keyVaultUri : The keyVaultUri field is required.
encryptionKey.keyVaultKeyName : The keyVaultKeyName field is required.

However, when defining parameters keyVaultUri and keyVaultKeyName from the error message in encryptionKey and removing parameters key_name and vault_uri which Microsoft documentation specifies are the available properties of class SearchResourceEncryptionKey , I get the following error (as expected):
NB: Error persisted even when these parameter name variations were tried: key_vault_uri and key_vault_key_name

Traceback (most recent call last):
  File "/Users/<redacted-project-path>/<redacted-filename>.py", line 1352, in setup_clients
    encryption_key_test = SearchResourceEncryptionKey(
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: SearchResourceEncryptionKey.__init__() missing 2 required keyword-only arguments: 'key_name' and 'vault_uri'

I also tried defining all of these parameters in encryptionKey , however I get the following warning and my original error of missing parameters:

WARNING - azure.search.documents.indexes._generated._serialization - keyVaultUri is not a known attribute of class <class 'azure.search.documents.indexes.models._models.SearchResourceEncryptionKey'> and will be ignored
azure.search.documents.indexes._generated._serialization - keyVaultKeyName is not a known attribute of class <class 'azure.search.documents.indexes.models._models.SearchResourceEncryptionKey'> and will be ignored

To Reproduce
Steps to reproduce the behaviour:

Assuming Blob Storage Account , Azure OpenAI Instance, Azure AI Search, Index and indexer all already exist and managed identity enabled with storage blob data read role (or necessary perms).

1. Install the library azure-search-documents==11.6.0b5
2. Define SearchResourceEncryptionKey object for encryption.
3. Create Indexer client.
4. Define skills, projection and skillset passing SearchResourceEncryptionKey object defined earlier.
5. Attempt to create skillset for above indexer.
6. Observe the "missing parameters" error.

from azure.search.documents.indexes import SearchIndexerClient
from azure.core.credentials import AzureKeyCredential
from azure.search.documents.indexes.models import (
    AzureOpenAIEmbeddingSkill,
    IndexProjectionMode,
    InputFieldMappingEntry,
    OutputFieldMappingEntry,
    SearchIndexer,
    SearchIndexerDataContainer,
    SearchIndexerDataSourceConnection,
    SearchIndexerIndexProjection,
    SearchIndexerIndexProjectionSelector,
    SearchIndexerIndexProjectionsParameters,
    SearchIndexerSkillset,
    SearchResourceEncryptionKey,
    SplitSkill,
)
# Initialize the client
indexer_client = SearchIndexerClient(endpoint="https://<your-search-service>.search.windows.net",
                             credential=AzureKeyCredential("<your-key>"))

# Define an encryption key
encryption_key_test = SearchResourceEncryptionKey(
    key_name="your-key-name",
    key_version="your-key-version",
    vault_uri="https://<your-keyvault-name>.vault.azure.net/",
    application_id="<your-client-app-id>",
    application_secret="<your-server-app-secret>",
)

# define skills, projection and skillset
split_skill = SplitSkill(
      description="Split skill to chunk documents",
      text_split_mode="pages",
      context="/document",
      maximum_page_length=2000,
      page_overlap_length=200,
      inputs=[
          InputFieldMappingEntry(name="text", source="/document/content"),
      ],
      outputs=[OutputFieldMappingEntry(name="textItems", target_name="pages")],
)

embedding_skill = AzureOpenAIEmbeddingSkill(
    description="Skill to generate embeddings via Azure OpenAI",
    context="/document/pages/*",
    resource_url="<azure_openai_url>", # resource uri for azure open ai instance
    deployment_name="<deployment-name>", # deployment name of embedding model deployed in azure open ai
    api_key="<azure_openai_key>", # key for azure open ai instance
    inputs=[
        InputFieldMappingEntry(name="text", source="/document/pages/*"),
    ],
    outputs=[OutputFieldMappingEntry(name="embedding", target_name="vectors")],
)

index_projection = SearchIndexerIndexProjection(
    selectors=[
        SearchIndexerIndexProjectionSelector(
            target_index_name="<index_name>",
            parent_key_field_name="parent_id",
            source_context="/document/pages/*",
            mappings=[
                InputFieldMappingEntry(name="content", source="/document/pages/*"),
                InputFieldMappingEntry(name="vector_embedding", source="/document/pages/*/vectors"),
            ],
        ),
    ],
    parameters=SearchIndexerIndexProjectionsParameters(
        projection_mode=IndexProjectionMode.SKIP_INDEXING_PARENT_DOCUMENTS
    ),
)

skillset = SearchIndexerSkillset(
        name="<skillset_name>",
        description="Skillset to chunk documents and generate embeddings",
        skills=[split_skill, embedding_skill],
        index_projection=index_projection,
        encryption_key=encryption_key_test,
)
            
# Attempt to create a skillset 
indexer_client.create_or_update_skillset(skillset)

Additional context
I use this encryption key in other places too i.e. when creating index, data source connection, indexer so it would be helpful if it can be checked this encryption key works for this version in the other places as i already found 1 bug while trying to create data source connection too. Thanks!

[github-actions]

Thank you for your feedback. Tagging and routing to the team member best able to assist.

[YVass1]

I saw the same error when using encryption key with SearchIndexer

Here is the code snippet to add on

indexer = SearchIndexer(
      name="indexer-name-example",
      description="Indexer to index documents and generate embeddings",
      # TODO Bug in creating skillset so commented out for now 
      # skillset_name="<skillset-name>",
      target_index_name="<index-name>",
      data_source_name="<data-source-connection>",
      encryption_key=encryption_key_test,
      schedule=IndexingSchedule(
          interval="PT1H", start_time="2024-09-12T22:04:02Z"
      ),
  )
  
indexer_client.create_or_update_indexer(indexer)

[YVass1]

Hi, is there an update ? Is there a new package release with the fix included now ?

[xiangyan99]

The fix is merged. It will be available in next release in about 2 weeks.

[YVass1]

Thanks, will that be a beta release or it is possible to release the fix earlier in a beta release ?

[xiangyan99]

That will be a beta release and if everything goes well, we will ship it on 8th.

[xiangyan99]

FYI. azure-search-documents 11.6.0b6 is shipped. https://pypi.org/project/azure-search-documents/11.6.0b6/

[github-actions]

Hi @YVass1. Thank you for opening this issue and giving us the opportunity to assist. We believe that this has been addressed. If you feel that further discussion is needed, please add a comment with the text "/unresolve" to remove the "issue-addressed" label and continue the conversation.

[github-actions]

Hi @YVass1, since you haven’t asked that we /unresolve the issue, we’ll close this out. If you believe further discussion is needed, please add a comment /unresolve to reopen the issue.