Question: I'm trying to create an embedding vector database with some .txt documents in my local folder. In particular I'm following this tutorial from the official page of LangChain: LangChain - Azure Cognitive Search and Azure OpenAI. I have followed all the steps of the tutorial and this is my Python script: # From https://python.langchain.com/docs/integrations/vectorstores/azuresearch import openai import os from langchain.embeddings import OpenAIEmbeddings from langchain.vectorstores.azuresearch import AzureSearch os.environ["OPENAI_API_TYPE"] = "azure" os.environ["OPENAI_API_BASE"] = "https://xxxxxx.openai.azure.com" os.environ["OPENAI_API_KEY"] = "xxxxxxxxx" os.environ["OPENAI_API_VERSION"] = "2023-05-15" model: str = "text-embedding-ada-002" vector_store_address: str = "https://xxxxxxx.search.windows.net" vector_store_password: str = "xxxxxxx" embeddings: OpenAIEmbeddings = OpenAIEmbeddings(deployment=model, chunk_size=1) index_name: str = "cognitive-search-openai-exercise-index" vector_store: AzureSearch = AzureSearch( azure_search_endpoint=vector_store_address, azure_search_key=vector_store_password, index_name=index_name, embedding_function=embeddings.embed_query, ) from langchain.document_loaders import TextLoader from langchain.text_splitter import CharacterTextSplitter loader = TextLoader("C:/Users/xxxxxxxx/azure_openai_cognitive_search_exercise/data/qna/a.txt", encoding="utf-8") documents = loader.load() text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) docs = text_splitter.split_documents(documents) vector_store.add_documents(documents=docs) # Perform a similarity search docs = vector_store.similarity_search( query="Who is Pippo Franco?", k=3, search_type="similarity", ) print(docs[0].page_content)  Now, when I run the script I get the following error:   vector_search_configuration is not a known attribute of class <class 'azure.search.documents.indexes.models._index.SearchField'> and will be ignored algorithm_configurations is not a known attribute of class <class 'azure.search.documents.indexes._generated.models._models_py3.VectorSearch'> and will be ignored Traceback (most recent call last): File "C:\Users\xxxxxxxxx\venv\Lib\site-packages\langchain\vectorstores\azuresearch.py", line 105, in _get_search_client index_client.get_index(name=index_name) File "C:\Users\xxxxxxx\venv\Lib\site-packages\azure\core\tracing\decorator.py", line 78, in wrapper_use_tracer return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\xxxxxxx\KYF\venv\Lib\site-packages\azure\search\documents\indexes\_search_index_client.py", line 145, in get_index result = self._client.indexes.get(name, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\xxxxxx\venv\Lib\site-packages\azure\core\tracing\decorator.py", line 78, in wrapper_use_tracer return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\xxxxxx\KYF\venv\Lib\site-packages\azure\search\documents\indexes\_generated\operations\_indexes_operations.py", line 864, in get map_error(status_code=response.status_code, response=response, error_map=error_map) File "C:\Users\xxxxxxxx\venv\Lib\site-packages\azure\core\exceptions.py", line 165, in map_error raise error azure.core.exceptions.ResourceNotFoundError: () No index with the name 'cognitive-search-openai-exercise-index' was found in the service 'cognitive-search-openai-exercise'. Code: Message: No index with the name 'cognitive-search-openai-exercise-index' was found in the service 'cognitive-search-openai-exercise'. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "c:\Users\xxxxxxx\venv\azure_openai_cognitive_search_exercise\test.py", line 25, in <module> vector_store: AzureSearch = AzureSearch( ^^^^^^^^^^^^ File "C:\Users\xxxxxxx\venv\Lib\site-packages\langchain\vectorstores\azuresearch.py", line 237, in __init__ self.client = _get_search_client( ^^^^^^^^^^^^^^^^^^^ File "C:\Users\xxxxxxxx\venv\Lib\site-packages\langchain\vectorstores\azuresearch.py", line 172, in _get_search_client index_client.create_index(index) File "C:\Users\xxxxxxx\venv\Lib\site-packages\azure\core\tracing\decorator.py", line 78, in wrapper_use_tracer return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\xxxxxxx\venv\Lib\site-packages\azure\search\documents\indexes\_search_index_client.py", line 220, in create_index result = self._client.indexes.create(patched_index, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\xxxxxxx\venv\Lib\site-packages\azure\core\tracing\decorator.py", line 78, in wrapper_use_tracer return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\xxxxxx\venv\Lib\site-packages\azure\search\documents\indexes\_generated\operations\_indexes_operations.py", line 402, in create raise HttpResponseError(response=response, model=error) azure.core.exceptions.HttpResponseError: (InvalidRequestParameter) The request is invalid. Details: definition : The vector field 'content_vector' must have the property 'vectorSearchConfiguration' set. Code: InvalidRequestParameter Message: The request is invalid. Details: definition : The vector field 'content_vector' must have the property 'vectorSearchConfiguration' set. Exception Details: (InvalidField) The vector field 'content_vector' must have the property 'vectorSearchConfiguration' set. Parameters: definition Code: InvalidField Message: The vector field 'content_vector' must have the property 'vectorSearchConfiguration' set. Parameters: definition    I have created an index manually from the Azure Cognitive Search Console, but I don't think this is the correct approach, as the script should automatically create a new index.

Answer: Please use pip install azure-search-documents==11.4.0b8 to ensure you are using the azure cognitive search python SDK compatible with LangChain.