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Data source - Azure AI Search

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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))