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--- title: Azure OpenAI embeddings store output binding for Azure Functions description: Learn how to use the Azure OpenAI embeddings store output binding to write searchable content to a semantic document store during function execution in Azure Functions. ms.topic: reference ms.custom: - build-2024 - devx-track-extended-java - devx-track-js - devx-track-python - devx-track-ts - build-2025 ms.collection: - ce-skilling-ai-copilot ms.date: 05/15/2025 ms.update-cycle: 180-days zone_pivot_groups: programming-languages-set-functions --- # Azure OpenAI embeddings store output binding for Azure Functions [!INCLUDE [preview-support](../../includes/functions-openai-support-limitations.md)] The Azure OpenAI embeddings store output binding allows you to write files to a semantic document store that can be referenced later in a semantic search. For information on setup and configuration details of the Azure OpenAI extension, see [Azure OpenAI extensions for Azure Functions](./functions-bindings-openai.md). To learn more about semantic ranking in Azure AI Search, see [Semantic ranking in Azure AI Search](/azure/search/semantic-search-overview). [!INCLUDE [functions-support-notes-samples-openai](../../includes/functions-support-notes-samples-openai.md)] ## Example ::: zone pivot="programming-language-csharp" This example writes an HTTP input stream to a semantic document store at the provided URL. :::code language="csharp" source="~/functions-openai-extension/samples/rag-aisearch/csharp-ooproc/FilePrompt.cs" range="17-21,29-66"::: ::: zone-end ::: zone pivot="programming-language-java" This example writes an HTTP input stream to a semantic document store at the provided URL. :::code language="java" source="~/functions-openai-extension/samples/rag-aisearch/java/src/main/java/com/azfs/FilePrompt.java" range="29-73"::: ::: zone-end ::: zone pivot="programming-language-javascript,programming-language-typescript" This example writes an HTTP input stream to a semantic document store at the provided URL. ::: zone-end ::: zone pivot="programming-language-javascript" :::code language="javascript" source="~/functions-openai-extension/samples/rag-aisearch/javascript/src/app.js" range="5-37"::: ::: zone-end ::: zone pivot="programming-language-typescript" :::code language="typescript" source="~/functions-openai-extension/samples/rag-aisearch/typescript/src/app.ts" range="4-40"::: ::: zone-end ::: zone pivot="programming-language-powershell" This example writes an HTTP input stream to a semantic document store at the provided URL. Here's the _function.json_ file for ingesting files: :::code language="json" source="~/functions-openai-extension/samples/rag-aisearch/powershell/IngestFile/function.json" ::: For more information about *function.json* file properties, see the [Configuration](#configuration) section. :::code language="powershell" source="~/functions-openai-extension/samples/rag-aisearch/powershell/IngestFile/run.ps1" ::: ::: zone-end ::: zone pivot="programming-language-python" This example writes an HTTP input stream to a semantic document store at the provided URL. :::code language="python" source="~/functions-openai-extension/samples/rag-aisearch/python/function_app.py" range="8-35"::: ::: zone-end <!--- End code examples section --> ::: zone pivot="programming-language-csharp" ## Attributes Apply the `EmbeddingsStoreOutput` attribute to define an embeddings store output binding, which supports these parameters: | Parameter | Description | | --------- | ----------- | | **Input** | The input string for which to generate embeddings. | | **AIConnectionName** | _Optional_. Gets or sets the name of the configuration section for AI service connectivity settings. For Azure OpenAI: If specified, looks for "Endpoint" and "Key" values in this configuration section. If not specified or the section doesn't exist, falls back to environment variables: AZURE_OPENAI_ENDPOINT and AZURE_OPENAI_KEY. For user-assigned managed identity authentication, this property is required. For OpenAI service (non-Azure), set the OPENAI_API_KEY environment variable.| | **EmbeddingsModel** | _Optional_. The ID of the model to use, which defaults to `text-embedding-ada-002`. You shouldn't change the model for an existing database. For more information, see [Usage](#usage). | | **MaxChunkLength** | _Optional_. The maximum number of characters used for chunking the input. For more information, see [Usage](#usage).| | **MaxOverlap** | _Optional_. Gets or sets the maximum number of characters to overlap between chunks.| | **InputType** | _Optional_. Gets the type of the input. | | **StoreConnectionName** | The name of an app setting or environment variable that contains the connection string value. This property supports binding expressions. | | **Collection** | The name of the collection or table or index to search. This property supports binding expressions.| ::: zone-end ::: zone pivot="programming-language-java" ## Annotations The `EmbeddingsStoreOutput` annotation enables you to define an embeddings store output binding, which supports these parameters: | Element | Description | | ------- | ----------- | | **name** | Gets or sets the name of the output binding. | | **input** | The input string for which to generate embeddings. | | **aiConnectionName** | _Optional_. Gets or sets the name of the configuration section for AI service connectivity settings. For Azure OpenAI: If specified, looks for "Endpoint" and "Key" values in this configuration section. If not specified or the section doesn't exist, falls back to environment variables: AZURE_OPENAI_ENDPOINT and AZURE_OPENAI_KEY. For user-assigned managed identity authentication, this property is required. For OpenAI service (non-Azure), set the OPENAI_API_KEY environment variable.| | **embeddingsModel** | _Optional_. The ID of the model to use, which defaults to `text-embedding-ada-002`. You shouldn't change the model for an existing database. For more information, see [Usage](#usage). | | **maxChunkLength** | _Optional_. The maximum number of characters used for chunking the input. For more information, see [Usage](#usage).| | **maxOverlap** | _Optional_. Gets or sets the maximum number of characters to overlap between chunks.| | **inputType** | _Optional_. Gets the type of the input. | | **storeConnectionName** | The name of an app setting or environment variable that contains the connection string value. This property supports binding expressions. | | **collection** | The name of the collection or table or index to search. This property supports binding expressions.| ::: zone-end ::: zone pivot="programming-language-python" ## Decorators <!--- Replace with typed decorator when available.--> During the preview, define the output binding as a `generic_output_binding` binding of type `semanticSearch`, which supports these parameters: |Parameter | Description | |---------|-------------| | **arg_name** | The name of the variable that represents the binding parameter. | | **input** | The input string for which to generate embeddings. | | **ai_connection_name** | _Optional_. Gets or sets the name of the configuration section for AI service connectivity settings. For Azure OpenAI: If specified, looks for "Endpoint" and "Key" values in this configuration section. If not specified or the section doesn't exist, falls back to environment variables: AZURE_OPENAI_ENDPOINT and AZURE_OPENAI_KEY. For user-assigned managed identity authentication, this property is required. For OpenAI service (non-Azure), set the OPENAI_API_KEY environment variable.| | **embeddings_model** | _Optional_. The ID of the model to use, which defaults to `text-embedding-ada-002`. You shouldn't change the model for an existing database. For more information, see [Usage](#usage). | | **maxChunkLength** | _Optional_. The maximum number of characters used for chunking the input. For more information, see [Usage](#usage).| | **max_overlap** | _Optional_. Gets or sets the maximum number of characters to overlap between chunks.| | **input_type** | Gets the type of the input. | | **store_connection_name** | The name of an app setting or environment variable that contains the connection string value. This property supports binding expressions. | | **collection** | The name of the collection or table or index to search. This property supports binding expressions.| ::: zone-end ::: zone pivot="programming-language-powershell" ## Configuration The binding supports these configuration properties that you set in the function.json file. |Property | Description | |-----------------------|-------------| | **type** | Must be `embeddingsStore`. | | **direction** | Must be `out`. | | **name** | The name of the output binding. | | **input** | The input string for which to generate embeddings. | | **aiConnectionName** | _Optional_. Gets or sets the name of the configuration section for AI service connectivity settings. For Azure OpenAI: If specified, looks for "Endpoint" and "Key" values in this configuration section. If not specified or the section doesn't exist, falls back to environment variables: AZURE_OPENAI_ENDPOINT and AZURE_OPENAI_KEY. For user-assigned managed identity authentication, this property is required. For OpenAI service (non-Azure), set the OPENAI_API_KEY environment variable.| | **embeddingsModel** | _Optional_. The ID of the model to use, which defaults to `text-embedding-ada-002`. You shouldn't change the model for an existing database. For more information, see [Usage](#usage). | | **maxChunkLength** | _Optional_. The maximum number of characters used for chunking the input. For more information, see [Usage](#usage).| | **maxOverlap** | _Optional_. Gets or sets the maximum number of characters to overlap between chunks.| | **inputType** | _Optional_. Gets the type of the input. | | **storeConnectionName** | The name of an app setting or environment variable that contains the connection string value. This property supports binding expressions. | | **collection** | The name of the collection or table or index to search. This property supports binding expressions.| ::: zone-end ::: zone pivot="programming-language-javascript,programming-language-typescript" ## Configuration The binding supports these properties, which are defined in your code: |Property | Description | |-----------------------|-------------| | **input** | The input string for which to generate embeddings. | | **aiConnectionName** | _Optional_. Gets or sets the name of the configuration section for AI service connectivity settings. For Azure OpenAI: If specified, looks for "Endpoint" and "Key" values in this configuration section. If not specified or the section doesn't exist, falls back to environment variables: AZURE_OPENAI_ENDPOINT and AZURE_OPENAI_KEY. For user-assigned managed identity authentication, this property is required. For OpenAI service (non-Azure), set the OPENAI_API_KEY environment variable.| | **embeddingsModel** | _Optional_. The ID of the model to use, which defaults to `text-embedding-ada-002`. You shouldn't change the model for an existing database. For more information, see [Usage](#usage). | | **maxChunkLength** | _Optional_. The maximum number of characters used for chunking the input. For more information, see [Usage](#usage).| | **maxOverlap** | _Optional_. Gets or sets the maximum number of characters to overlap between chunks.| | **inputType** | _Optional_. Gets the type of the input. | | **storeConnectionName** | The name of an app setting or environment variable that contains the connection string value. This property supports binding expressions. | | **collection** | The name of the collection or table or index to search. This property supports binding expressions.| ::: zone-end ## Usage See the [Example section](#example) for complete examples. ## Related content + [Semantic search samples](https://github.com/Azure/azure-functions-openai-extension/tree/main/samples/rag-aisearch) + [Azure OpenAI extensions for Azure Functions](functions-bindings-openai.md) + [Azure OpenAI semantic search input binding for Azure Functions](functions-bindings-openai-semanticsearch-input.md)