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Data source - Azure Machine Learning index (preview)

  • आलेख

The configurable options of Azure Machine Learning index when using Azure OpenAI On Your Data. This data source is supported in API version 2024-02-15-preview.

Name Type Required Description
parameters Parameters True The parameters to use when configuring Azure Machine Learning index.
type string True Must be azure_ml_index.

Parameters

Name Type Required Description
project_resource_id string True The resource ID of the Azure Machine Learning project.
name string True The Azure Machine Learning index name.
version string True The version of the Azure Machine Learning index.
authentication One of AccessTokenAuthenticationOptions, SystemAssignedManagedIdentityAuthenticationOptions, UserAssignedManagedIdentityAuthenticationOptions True The authentication method to use when accessing the defined data source.
in_scope boolean False Whether queries should be restricted to use of indexed data. Default is True.
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.
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.
filter string False Search filter. Only supported if the Azure Machine Learning index is of type Azure Search.

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.

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.

Examples

Prerequisites:

  • Configure the role assignments from Azure OpenAI system assigned managed identity to Azure Machine Learning workspace resource. Required role: AzureML Data Scientist.
  • 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, ProjectResourceId, IndexName, IndexVersion.
  • Run export MSYS_NO_PATHCONV=1 if you're using MINGW.
export AzureOpenAIEndpoint=https://example.openai.azure.com/
export ChatCompletionsDeploymentName=turbo
export ProjectResourceId='/subscriptions/{subscription-id}/resourceGroups/{resource-group-name}/providers/Microsoft.MachineLearningServices/workspaces/{workspace-id}'
export IndexName=testamlindex
export IndexVersion=2

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")
project_resource_id = os.environ.get("ProjectResourceId")
index_name = os.environ.get("IndexName")
index_version = os.environ.get("IndexVersion")

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="2024-02-15-preview",
)

completion = client.chat.completions.create(
    model=deployment,
    messages=[
        {
            "role": "user",
            "content": "Who is DRI?",
        },
    ],
    extra_body={
        "data_sources": [
            {
                "type": "azure_ml_index",
                "parameters": {
                    "project_resource_id": project_resource_id,
                    "name": index_name,
                    "version": index_version,
                    "authentication": {
                        "type": "system_assigned_managed_identity"
                    },
                }
            }
        ]
    }
)

print(completion.model_dump_json(indent=2))