ImportError: cannot import name 'HnswVectorSearchAlgorithmConfiguration' from 'azure.search.documents.indexes.models'
Labels: name: area: vector store, name: auto:bug

### System Info

I tried to use langchain with Azure Cognitive Search as vector store and got the following Import Error.

langchain version: 0.0.276
azure documents: 11.4.0b8
python version: 3.8


### Who can help?

_No response_

### Information

- [ ] The official example notebooks/scripts
- [X] My own modified scripts

### Related Components

- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [X] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async

### Reproduction


I tried to use the Azure Cognitive Search as vector store

```
    model: str = "text-embedding-ada-002"
    search_service = os.environ["AZURE_COGNITIVE_SEARCH_SERVICE_NAME"]
    search_api_key = os.environ["AZURE_COGNITIVE_SEARCH_API_KEY"]
    vector_store_address: str = f"https://{search_service}.search.windows.net"
    vector_store_password: str = search_api_key

    # define embedding model for calculating the embeddings
    model: str = "text-embedding-ada-002"
    embeddings: OpenAIEmbeddings = OpenAIEmbeddings(deployment=model, chunk_size=1)
    embedding_function = embeddings.embed_query

    # define schema of the json file stored on the index
    fields = [
            SimpleField(
                name="id",
                type=SearchFieldDataType.String,
                key=True,
                filterable=True,
            ),
            SearchableField(
                name="content",
                type=SearchFieldDataType.String,
                searchable=True,
            ),
            SearchField(
                name="content_vector",
                type=SearchFieldDataType.Collection(SearchFieldDataType.Single),
                searchable=True,
                vector_search_dimensions=len(embedding_function("Text")),
                vector_search_configuration="default",
            ),
            SearchableField(
                name="metadata",
                type=SearchFieldDataType.String,
                searchable=True,
            ),
        ]    
    
    vector_store: AzureSearch = AzureSearch(
        azure_search_endpoint=vector_store_address,
        azure_search_key=vector_store_password,
        index_name=index_name,
        embedding_function=embedding_function,
        fields=fields,
    )


```

And I got the following import error

```
Cell In[17], line 72, in azure_search_by_index(question, index_name)
     21 # define schema of the json file stored on the index
     22 fields = [
     23         SimpleField(
     24             name="id",
   (...)
     69         ),
     70     ]    
---> 72 vector_store: AzureSearch = AzureSearch(
     73     azure_search_endpoint=vector_store_address,
     74     azure_search_key=vector_store_password,
     75     index_name=index_name,
     76     embedding_function=embedding_function,
     77     fields=fields,
     78 )
     80 relevant_documentation = vector_store.similarity_search(query=question, k=1, search_type="similarity")
     82 context = "\n".join([doc.page_content for doc in relevant_documentation])[:10000]

File /anaconda/envs/jupyter_env/lib/python3.8/site-packages/langchain/vectorstores/azuresearch.py:234, in AzureSearch.__init__(self, azure_search_endpoint, azure_search_key, index_name, embedding_function, search_type, semantic_configuration_name, semantic_query_language, fields, vector_search, semantic_settings, scoring_profiles, default_scoring_profile, **kwargs)
    232 if "user_agent" in kwargs and kwargs["user_agent"]:
    233     user_agent += " " + kwargs["user_agent"]
--> 234 self.client = _get_search_client(
    235     azure_search_endpoint,
    236     azure_search_key,
    237     index_name,
    238     semantic_configuration_name=semantic_configuration_name,
    239     fields=fields,
    240     vector_search=vector_search,
    241     semantic_settings=semantic_settings,
    242     scoring_profiles=scoring_profiles,
    243     default_scoring_profile=default_scoring_profile,
    244     default_fields=default_fields,
    245     user_agent=user_agent,
    246 )
    247 self.search_type = search_type
    248 self.semantic_configuration_name = semantic_configuration_name

File /anaconda/envs/jupyter_env/lib/python3.8/site-packages/langchain/vectorstores/azuresearch.py:83, in _get_search_client(endpoint, key, index_name, semantic_configuration_name, fields, vector_search, semantic_settings, scoring_profiles, default_scoring_profile, default_fields, user_agent)
     81 from azure.search.documents import SearchClient
     82 from azure.search.documents.indexes import SearchIndexClient
---> 83 from azure.search.documents.indexes.models import (
     84     HnswVectorSearchAlgorithmConfiguration,
     85     PrioritizedFields,
     86     SearchIndex,
     87     SemanticConfiguration,
     88     SemanticField,
     89     SemanticSettings,
     90     VectorSearch,
     91 )
     93 default_fields = default_fields or []
     94 if key is None:

ImportError: cannot import name 'HnswVectorSearchAlgorithmConfiguration' from 'azure.search.documents.indexes.models' (/anaconda/envs/jupyter_env/lib/python3.8/site-packages/azure/search/documents/indexes/models/__init__.py)
```

### Expected behavior

No import error