Data source - Azure Cosmos DB for MongoDB vCore

The configurable options of Azure Cosmos DB for MongoDB vCore 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 Cosmos DB for MongoDB vCore.
type	string	True	Must be azure_cosmos_db.

Parameters

Name	Type	Required	Description
database_name	string	True	The MongoDB vCore database name to use with Azure Cosmos DB.
container_name	string	True	The name of the Azure Cosmos DB resource container.
index_name	string	True	The MongoDB vCore index name to use with Azure Cosmos DB.
fields_mapping	FieldsMappingOptions	True	Customized field mapping behavior to use when interacting with the search index.
authentication	ConnectionStringAuthenticationOptions	True	The authentication method to use when accessing the defined data source.
embedding_dependency	One of DeploymentNameVectorizationSource, EndpointVectorizationSource	True	The embedding dependency for vector search.
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.

Connection string authentication options

The authentication options for Azure OpenAI On Your Data when using a connection string.

Name	Type	Required	Description
connection_string	string	True	The connection string to use for authentication.
type	string	True	Must be connection_string.

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.

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.

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.

Fields mapping options

The settings to control how fields are processed.

Name	Type	Required	Description
content_fields	string[]	True	The names of index fields that should be treated as content.
vector_fields	string[]	True	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.

Examples

Prerequisites:

• 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,ConnectionString, Database, Container, Index, EmbeddingDeploymentName.

Note

The following is for example only. If you use a connection string, store it securely somewhere else, such as in Azure Key Vault. Don't include the API key directly in your code, and never post it publicly.

export AzureOpenAIEndpoint=https://example.openai.azure.com/
export ChatCompletionsDeploymentName=turbo
export ConnectionString='<db-connection-string>'
export Database=testdb
export Container=testcontainer
export Index=testindex
export EmbeddingDeploymentName=ada

Python 1.x

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")
connection_string = os.environ.get("ConnectionString")
database = os.environ.get("Database")
container = os.environ.get("Container")
index = os.environ.get("Index")
embedding_deployment_name = os.environ.get("EmbeddingDeploymentName")

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_cosmos_db",
                "parameters": {
                    "authentication": {
                        "type": "connection_string",
                        "connection_string": connection_string
                    },
                    "database_name": database,
                    "container_name": container,
                    "index_name": index,
                    "fields_mapping": {
                        "content_fields": [
                            "content"
                        ],
                        "vector_fields": [
                            "contentvector"
                        ]
                    },
                    "embedding_dependency": {
                        "type": "deployment_name",
                        "deployment_name": embedding_deployment_name
                    }
                }
            }
        ],
    }
)

print(completion.model_dump_json(indent=2))

REST

az rest --method POST \
 --uri $AzureOpenAIEndpoint/openai/deployments/$ChatCompletionsDeploymentName/chat/completions?api-version=2024-02-01 \
 --resource https://cognitiveservices.azure.com/ \
 --body \
'
{
    "data_sources": [
      {
        "type": "azure_cosmos_db",
        "parameters": {
          "authentication": {
            "type": "connection_string",
            "connection_string": "'$ConnectionString'"
          },
          "database_name": "'$Database'",
          "container_name": "'$Container'",
          "index_name": "'$Index'",
          "fields_mapping": {
            "content_fields": [
              "content"
            ],
            "vector_fields": [
              "contentvector"
            ]
          },
          "embedding_dependency": {
            "type": "deployment_name",
            "deployment_name": "'$EmbeddingDeploymentName'"
          }
        }
      }
    ],
    "messages": [
      {
        "role": "user",
        "content": "Who is DRI?"
      }
    ]
}
'