| title | Azure OpenAI embeddings input binding for Azure Functions | ||||||
|---|---|---|---|---|---|---|---|
| description | Learn how to use the Azure OpenAI embeddings input binding to generate embeddings during function execution in Azure Functions. | ||||||
| ms.topic | reference | ||||||
| ms.custom |
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| ms.collection |
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| ms.date | 05/15/2025 | ||||||
| ms.update-cycle | 180-days | ||||||
| zone_pivot_groups | programming-languages-set-functions |
[!INCLUDE preview-support]
The Azure OpenAI embeddings input binding allows you to generate embeddings for inputs. The binding can generate embeddings from files or raw text inputs.
For information on setup and configuration details of the Azure OpenAI extension, see Azure OpenAI extensions for Azure Functions. To learn more about embeddings in Azure OpenAI Service, see Understand embeddings in Azure OpenAI Service.
[!INCLUDE functions-support-notes-samples-openai]
::: zone pivot="programming-language-csharp"
This example shows how to generate embeddings for a raw text string.
:::code language="csharp" source="~/functions-openai-extension/samples/embeddings/csharp-ooproc/Embeddings/EmbeddingsGenerator.cs" range="25-57":::
This example shows how to retrieve embeddings stored at a specified file that is accessible to the function.
:::code language="csharp" source="~/functions-openai-extension/samples/embeddings/csharp-ooproc/Embeddings/EmbeddingsGenerator.cs" range="63-78":::
::: zone-end
::: zone pivot="programming-language-java"
This example shows how to generate embeddings for a raw text string.
:::code language="java" source="~/functions-openai-extension/samples/embeddings/java/src/main/java/com/azfs/EmbeddingsGenerator.java" range="26-53":::
This example shows how to retrieve embeddings stored at a specified file that is accessible to the function.
:::code language="java" source="~/functions-openai-extension/samples/embeddings/java/src/main/java/com/azfs/EmbeddingsGenerator.java" range="59-86":::
::: zone-end
::: zone pivot="programming-language-javascript,programming-language-typescript"
This example shows how to generate embeddings for a raw text string.
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:::code language="javascript" source="~/functions-openai-extension/samples/embeddings/javascript/src/app.js" range="3-27":::
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:::code language="typescript" source="~/functions-openai-extension/samples/embeddings/typescript/src/app.ts" range="3-31":::
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::: zone pivot="programming-language-javascript,programming-language-typescript"
This example shows how to generate embeddings for a raw text string.
::: zone-end
::: zone pivot="programming-language-javascript"
:::code language="javascript" source="~/functions-openai-extension/samples/embeddings/javascript/src/app.js" range="29-54":::
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:::code language="typescript" source="~/functions-openai-extension/samples/embeddings/typescript/src/app.ts" range="33-62":::
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::: zone pivot="programming-language-powershell"
This example shows how to generate embeddings for a raw text string.
Here's the function.json file for generating the embeddings:
:::code language="json" source="~/functions-openai-extension/samples/embeddings/powershell/GenerateEmbeddings/function.json" :::
For more information about function.json file properties, see the Configuration section.
:::code language="powershell" source="~/functions-openai-extension/samples/embeddings/powershell/GenerateEmbeddings/run.ps1" :::
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::: zone pivot="programming-language-python"
This example shows how to generate embeddings for a raw text string.
:::code language="python" source="~/functions-openai-extension/samples/embeddings/python/function_app.py" range="8-27":::
::: zone-end
::: zone pivot="programming-language-csharp"
Apply the EmbeddingsInput attribute to define an embeddings input 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. |
| MaxChunkLength | Optional. The maximum number of characters used for chunking the input. For more information, see Usage. |
| MaxOverlap | Optional. Gets or sets the maximum number of characters to overlap between chunks. |
| InputType | Optional. Gets the type of the input. |
::: zone-end ::: zone pivot="programming-language-java"
The EmbeddingsInput annotation enables you to define an embeddings input binding, which supports these parameters:
| Element | Description |
|---|---|
| name | Gets or sets the name of the input 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. |
| maxChunkLength | Optional. The maximum number of characters used for chunking the input. For more information, see Usage. |
| maxOverlap | Optional. Gets or sets the maximum number of characters to overlap between chunks. |
| inputType | Optional. Gets the type of the input. |
::: zone-end
::: zone pivot="programming-language-python"
During the preview, define the input binding as a generic_input_binding binding of type embeddings, which supports these parameters: embeddings decorator 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. |
| maxChunkLength | Optional. The maximum number of characters used for chunking the input. For more information, see Usage. |
| max_overlap | Optional. Gets or sets the maximum number of characters to overlap between chunks. |
| input_type | Gets the type of the input. |
::: zone-end ::: zone pivot="programming-language-powershell"
The binding supports these configuration properties that you set in the function.json file.
| Property | Description |
|---|---|
| type | Must be EmbeddingsInput. |
| direction | Must be in. |
| name | The name of the input 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. |
| maxChunkLength | Optional. The maximum number of characters used for chunking the input. For more information, see Usage. |
| maxOverlap | Optional. Gets or sets the maximum number of characters to overlap between chunks. |
| inputType | Optional. Gets the type of the input. |
::: zone-end
::: zone pivot="programming-language-javascript,programming-language-typescript"
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. |
| maxChunkLength | Optional. The maximum number of characters used for chunking the input. For more information, see Usage. |
| maxOverlap | Optional. Gets or sets the maximum number of characters to overlap between chunks. |
| inputType | Optional. Gets the type of the input. |
::: zone-end
See the Example section for complete examples.
Changing the default embeddings model changes the way that embeddings are stored in the vector database. Changing the default model can cause the lookups to start misbehaving when they don't match the rest of the data that was previously ingested into the vector database. The default model for embeddings is text-embedding-ada-002.
When calculating the maximum character length for input chunks, consider that the maximum input tokens allowed for second-generation input embedding models like text-embedding-ada-002 is 8191. A single token is approximately four characters in length (in English), which translates to roughly 32,000 (English) characters of input that can fit into a single chunk.