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Embedding
Introduction
OpenAI's embedding models convert text into dense vector representations for various NLP tasks. See the OpenAI Embeddings API for more information.
Prerequisite
Create OpenAI resources:
-
OpenAI
Sign up account OpenAI website Login and Find personal API key
-
Azure OpenAI (AOAI)
Create Azure OpenAI resources with instruction
Connections
Setup connections to provide resources in embedding tool.
| Type | Name | API KEY | API Type | API Version |
|---|---|---|---|---|
| OpenAI | Required | Required | - | - |
| AzureOpenAI | Required | Required | Required | Required |
Inputs
| Name | Type | Description | Required |
|---|---|---|---|
| input | string | the input text to embed | Yes |
| connection | string | the connection for the embedding tool use to provide resources | Yes |
| model/deployment_name | string | instance of the text-embedding engine to use. Fill in model name if you use OpenAI connection, or deployment name if use Azure OpenAI connection. | Yes |
Outputs
| Return Type | Description |
|---|---|
| list | The vector representations for inputs |
The following is an example response returned by the embedding tool:
Output
[-0.005744616035372019,
-0.007096089422702789,
-0.00563855143263936,
-0.005272455979138613,
-0.02355326898396015,
0.03955197334289551,
-0.014260607771575451,
-0.011810848489403725,
-0.023170066997408867,
-0.014739611186087132,
...]