Data source - Azure AI Search
The configurable options of Azure AI Search when using Azure OpenAI On Your Data. This data source is supported in API version 2024-02-01
.
Name | Type | Required | Description |
---|---|---|---|
parameters |
Parameters | True | The parameters to use when configuring Azure Search. |
type |
string | True | Must be azure_search . |
Parameters
Name | Type | Required | Description |
---|---|---|---|
endpoint |
string | True | The absolute endpoint path for the Azure Search resource to use. |
index_name |
string | True | The name of the index to use in the referenced Azure Search resource. |
authentication |
One of ApiKeyAuthenticationOptions, SystemAssignedManagedIdentityAuthenticationOptions, UserAssignedManagedIdentityAuthenticationOptions, onYourDataAccessTokenAuthenticationOptions | True | The authentication method to use when accessing the defined data source. |
embedding_dependency |
One of DeploymentNameVectorizationSource, EndpointVectorizationSource | False | The embedding dependency for vector search. Required when query_type is vector , vector_simple_hybrid , or vector_semantic_hybrid . |
fields_mapping |
FieldsMappingOptions | False | Customized field mapping behavior to use when interacting with the search index. |
filter |
string | False | Search filter. |
in_scope |
boolean | False | Whether queries should be restricted to use of indexed data. Default is True . |
query_type |
QueryType | False | The query type to use with Azure Search. Default is simple |
role_information |
string | False | Give the model instructions about how it should behave and any context it should reference when generating a response. You can describe the assistant's personality and tell it how to format responses. |
semantic_configuration |
string | False | The semantic configuration for the query. Required when query_type is semantic or vector_semantic_hybrid . |
strictness |
integer | False | The configured strictness of the search relevance filtering. The higher of strictness, the higher of the precision but lower recall of the answer. Default is 3 . |
top_n_documents |
integer | False | The configured top number of documents to feature for the configured query. Default is 5 . |
max_search_queries |
integer | False | The max number of rewritten queries should be send to search provider for one user message. If not specified, the system will decide the number of queries to send. |
allow_partial_result |
integer | False | If specified as true, the system will allow partial search results to be used and the request fails if all the queries fail. If not specified, or specified as false, the request will fail if any search query fails. |
include_contexts |
array | False | The included properties of the output context. If not specified, the default value is citations and intent . Values can be citations ,intent , all_retrieved_documents . |
API key authentication options
The authentication options for Azure OpenAI On Your Data when using an API key.
Name | Type | Required | Description |
---|---|---|---|
key |
string | True | The API key to use for authentication. |
type |
string | True | Must be api_key . |
System assigned managed identity authentication options
The authentication options for Azure OpenAI On Your Data when using a system-assigned managed identity.
Name | Type | Required | Description |
---|---|---|---|
type |
string | True | Must be system_assigned_managed_identity . |
User assigned managed identity authentication options
The authentication options for Azure OpenAI On Your Data when using a user-assigned managed identity.
Name | Type | Required | Description |
---|---|---|---|
managed_identity_resource_id |
string | True | The resource ID of the user-assigned managed identity to use for authentication. |
type |
string | True | Must be user_assigned_managed_identity . |
Access token authentication options
The authentication options for Azure OpenAI On Your Data when using access token.
Name | Type | Required | Description |
---|---|---|---|
access_token |
string | True | The access token to use for authentication. |
type |
string | True | Must be access_token . |
Deployment name vectorization source
The details of the vectorization source, used by Azure OpenAI On Your Data when applying vector search. This vectorization source is based on an internal embeddings model deployment name in the same Azure OpenAI resource. This vectorization source enables you to use vector search without Azure OpenAI api-key and without Azure OpenAI public network access.
Name | Type | Required | Description |
---|---|---|---|
deployment_name |
string | True | The embedding model deployment name within the same Azure OpenAI resource. |
type |
string | True | Must be deployment_name . |
dimensions |
integer | False | The number of dimensions the embeddings should have. Only supported in text-embedding-3 and later models. |
Endpoint vectorization source
The details of the vectorization source, used by Azure OpenAI On Your Data when applying vector search. This vectorization source is based on the Azure OpenAI embedding API endpoint.
Name | Type | Required | Description |
---|---|---|---|
endpoint |
string | True | Specifies the resource endpoint URL from which embeddings should be retrieved. It should be in the format of https://{YOUR_RESOURCE_NAME}.openai.azure.com/openai/deployments/YOUR_DEPLOYMENT_NAME/embeddings . The api-version query parameter isn't allowed. |
authentication |
ApiKeyAuthenticationOptions | True | Specifies the authentication options to use when retrieving embeddings from the specified endpoint. |
type |
string | True | Must be endpoint . |
dimensions |
integer | False | The number of dimensions the embeddings should have. Only supported in text-embedding-3 and later models. |
Fields mapping options
Optional settings to control how fields are processed when using a configured Azure Search resource.
Name | Type | Required | Description |
---|---|---|---|
content_fields |
string[] | False | The names of index fields that should be treated as content. |
vector_fields |
string[] | False | The names of fields that represent vector data. |
content_fields_separator |
string | False | The separator pattern that content fields should use. Default is \n . |
filepath_field |
string | False | The name of the index field to use as a filepath. |
title_field |
string | False | The name of the index field to use as a title. |
url_field |
string | False | The name of the index field to use as a URL. |
Query type
The type of Azure Search retrieval query that should be executed when using it as an Azure OpenAI On Your Data.
Enum Value | Description |
---|---|
simple |
Represents the default, simple query parser. |
semantic |
Represents the semantic query parser for advanced semantic modeling. |
vector |
Represents vector search over computed data. |
vector_simple_hybrid |
Represents a combination of the simple query strategy with vector data. |
vector_semantic_hybrid |
Represents a combination of semantic search and vector data querying. |
Examples
Prerequisites:
- Configure the role assignments from Azure OpenAI system assigned managed identity to Azure search service. Required roles:
Search Index Data Reader
,Search Service Contributor
. - Configure the role assignments from the user to the Azure OpenAI resource. Required role:
Cognitive Services OpenAI User
. - Install Az CLI, and run
az login
. - Define the following environment variables:
AzureOpenAIEndpoint
,ChatCompletionsDeploymentName
,SearchEndpoint
,SearchIndex
.
export AzureOpenAIEndpoint=https://example.openai.azure.com/
export ChatCompletionsDeploymentName=turbo
export SearchEndpoint=https://example.search.windows.net
export SearchIndex=example-index
Install the latest pip packages openai
, azure-identity
.
import os
from openai import AzureOpenAI
from azure.identity import DefaultAzureCredential, get_bearer_token_provider
endpoint = os.environ.get("AzureOpenAIEndpoint")
deployment = os.environ.get("ChatCompletionsDeploymentName")
search_endpoint = os.environ.get("SearchEndpoint")
search_index = os.environ.get("SearchIndex")
token_provider = get_bearer_token_provider(DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default")
client = AzureOpenAI(
azure_endpoint=endpoint,
azure_ad_token_provider=token_provider,
api_version="2024-02-01",
)
completion = client.chat.completions.create(
model=deployment,
messages=[
{
"role": "user",
"content": "Who is DRI?",
},
],
extra_body={
"data_sources": [
{
"type": "azure_search",
"parameters": {
"endpoint": search_endpoint,
"index_name": search_index,
"authentication": {
"type": "system_assigned_managed_identity"
}
}
}
]
}
)
print(completion.model_dump_json(indent=2))