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,
...]