Update azuresearch.py following recent change from azure-search-documents library (#13472)

- **Description:** 

Reference library azure-search-documents has been adapted in version
11.4.0:

1. Notebook explaining Azure AI Search updated with most recent info
2. HnswVectorSearchAlgorithmConfiguration --> HnswAlgorithmConfiguration
3. PrioritizedFields(prioritized_content_fields) -->
SemanticPrioritizedFields(content_fields)
4. SemanticSettings --> SemanticSearch
5. VectorSearch(algorithm_configurations) -->
VectorSearch(configurations)

--> Changes now reflected on Langchain: default vector search config
from langchain is now compatible with officially released library from
Azure.

  - **Issue:**
Issue creating a new index (due to wrong class used for default vector
search configuration) if using latest version of azure-search-documents
with current langchain version
  - **Dependencies:** azure-search-documents>=11.4.0,
  - **Tag maintainer:** ,

---------

Co-authored-by: Erick Friis <erick@langchain.dev>

docs/docs/integrations/vectorstores/azuresearch.ipynb

@@ -6,18 +6,17 @@
     "collapsed": false
    },
    "source": [
-    "# Azure Cognitive Search\n",
+    "# Azure AI Search\n",
     "\n",
-    "[Azure Cognitive Search](https://learn.microsoft.com/azure/search/search-what-is-azure-search) (formerly known as `Azure Search`) is a cloud search service that gives developers infrastructure, APIs, and tools for building a rich search experience over private, heterogeneous content in web, mobile, and enterprise applications.\n",
+    "[Azure AI Search](https://learn.microsoft.com/azure/search/search-what-is-azure-search) (formerly known as `Azure Search` and `Azure Cognitive Search`) is a cloud search service that gives developers infrastructure, APIs, and tools for building a rich search experience over private, heterogeneous content in web, mobile, and enterprise applications.\n",
-    "\n",
+    "\n"
-    "Vector search is currently in public preview. It's available through the Azure portal, preview REST API and beta client libraries. [More info](https://learn.microsoft.com/en-us/azure/search/vector-search-overview) Beta client libraries are subject to potential breaking changes, please be sure to use the SDK package version identified below. azure-search-documents==11.4.0b8"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Install Azure Cognitive Search SDK"
+    "# Install Azure AI Search SDK"
    ]
   },
   {
@@ -26,7 +25,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!pip install azure-search-documents==11.4.0b8\n",
+    "!pip install azure-search-documents\n",
     "!pip install azure-identity"
    ]
   },

libs/langchain/langchain/vectorstores/azuresearch.py

@@ -14,6 +14,7 @@ from typing import (
     Optional,
     Tuple,
     Type,
+    Union,
 )
 
 import numpy as np
@@ -36,10 +37,13 @@ if TYPE_CHECKING:
     from azure.search.documents.indexes.models import (
         ScoringProfile,
         SearchField,
-        SemanticSettings,
         VectorSearch,
     )
 
+    try:
+        from azure.search.documents.indexes.models import SemanticSearch
+    except ImportError:
+        from azure.search.documents.indexes.models import SemanticSettings  # <11.4.0
 
 # Allow overriding field names for Azure Search
 FIELDS_ID = get_from_env(
@@ -69,7 +73,7 @@ def _get_search_client(
     semantic_configuration_name: Optional[str] = None,
     fields: Optional[List[SearchField]] = None,
     vector_search: Optional[VectorSearch] = None,
-    semantic_settings: Optional[SemanticSettings] = None,
+    semantic_settings: Optional[Union[SemanticSearch, SemanticSettings]] = None,
     scoring_profiles: Optional[List[ScoringProfile]] = None,
     default_scoring_profile: Optional[str] = None,
     default_fields: Optional[List[SearchField]] = None,
@@ -81,15 +85,30 @@ def _get_search_client(
     from azure.search.documents import SearchClient
     from azure.search.documents.indexes import SearchIndexClient
     from azure.search.documents.indexes.models import (
-        HnswVectorSearchAlgorithmConfiguration,
-        PrioritizedFields,
         SearchIndex,
         SemanticConfiguration,
         SemanticField,
-        SemanticSettings,
         VectorSearch,
     )
 
+    # class names changed for versions >= 11.4.0
+    try:
+        from azure.search.documents.indexes.models import (
+            HnswAlgorithmConfiguration,  # HnswVectorSearchAlgorithmConfiguration is old
+            SemanticPrioritizedFields,  # PrioritizedFields outdated
+            SemanticSearch,  # SemanticSettings outdated
+        )
+
+        NEW_VERSION = True
+    except ImportError:
+        from azure.search.documents.indexes.models import (
+            HnswVectorSearchAlgorithmConfiguration,
+            PrioritizedFields,
+            SemanticSettings,
+        )
+
+        NEW_VERSION = False
+
     default_fields = default_fields or []
     if key is None:
         credential = DefaultAzureCredential()
@@ -135,34 +154,71 @@ def _get_search_client(
             fields = default_fields
         # Vector search configuration
         if vector_search is None:
-            vector_search = VectorSearch(
+            if NEW_VERSION:
-                algorithm_configurations=[
+                # >= 11.4.0:
-                    HnswVectorSearchAlgorithmConfiguration(
+                #   VectorSearch(algorithm_configuration) --> VectorSearch(algorithms)
-                        name="default",
+                # HnswVectorSearchAlgorithmConfiguration --> HnswAlgorithmConfiguration
-                        kind="hnsw",
+                vector_search = VectorSearch(
-                        parameters={  # type: ignore
+                    algorithms=[
-                            "m": 4,
+                        HnswAlgorithmConfiguration(
-                            "efConstruction": 400,
+                            name="default",
-                            "efSearch": 500,
+                            kind="hnsw",
-                            "metric": "cosine",
+                            parameters={  # type: ignore
-                        },
+                                "m": 4,
-                    )
+                                "efConstruction": 400,
-                ]
+                                "efSearch": 500,
-            )
+                                "metric": "cosine",
+                            },
+                        )
+                    ]
+                )
+            else:  # < 11.4.0
+                vector_search = VectorSearch(
+                    algorithm_configurations=[
+                        HnswVectorSearchAlgorithmConfiguration(
+                            name="default",
+                            kind="hnsw",
+                            parameters={  # type: ignore
+                                "m": 4,
+                                "efConstruction": 400,
+                                "efSearch": 500,
+                                "metric": "cosine",
+                            },
+                        )
+                    ]
+                )
+
         # Create the semantic settings with the configuration
         if semantic_settings is None and semantic_configuration_name is not None:
-            semantic_settings = SemanticSettings(
+            if NEW_VERSION:
-                configurations=[
+                # <=11.4.0: SemanticSettings --> SemanticSearch
-                    SemanticConfiguration(
+                # PrioritizedFields(prioritized_content_fields)
-                        name=semantic_configuration_name,
+                #   --> SemanticPrioritizedFields(content_fields)
-                        prioritized_fields=PrioritizedFields(
+                semantic_settings = SemanticSearch(
-                            prioritized_content_fields=[
+                    configurations=[
-                                SemanticField(field_name=FIELDS_CONTENT)
+                        SemanticConfiguration(
-                            ],
+                            name=semantic_configuration_name,
-                        ),
+                            prioritized_fields=SemanticPrioritizedFields(
-                    )
+                                content_fields=[
-                ]
+                                    SemanticField(field_name=FIELDS_CONTENT)
-            )
+                                ],
+                            ),
+                        )
+                    ]
+                )
+            else:  # < 11.4.0
+                semantic_settings = SemanticSettings(
+                    configurations=[
+                        SemanticConfiguration(
+                            name=semantic_configuration_name,
+                            prioritized_fields=PrioritizedFields(
+                                prioritized_content_fields=[
+                                    SemanticField(field_name=FIELDS_CONTENT)
+                                ],
+                            ),
+                        )
+                    ]
+                )
         # Create the search index with the semantic settings and vector search
         index = SearchIndex(
             name=index_name,
@@ -196,7 +252,7 @@ class AzureSearch(VectorStore):
         semantic_query_language: str = "en-us",
         fields: Optional[List[SearchField]] = None,
         vector_search: Optional[VectorSearch] = None,
-        semantic_settings: Optional[SemanticSettings] = None,
+        semantic_settings: Optional[Union[SemanticSearch, SemanticSettings]] = None,
         scoring_profiles: Optional[List[ScoringProfile]] = None,
         default_scoring_profile: Optional[str] = None,
         **kwargs: Any,