Using Embeddings API
Scaleway Generative APIs are designed as a drop-in replacement for the OpenAI APIs. If you have clustering or classification tasks already using one of OpenAI's client libraries, you can easily configure it to point to Scaleway Embeddings API, and get your existing applications running with open-weight embedding models hosted at Scaleway.
Create embeddings
Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.
Request sample:
curl https://api.scaleway.ai/v1/embeddings \
-H "Authorization: Bearer $SCW_SECRET_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "bge-multilingual-gemma2",
"input": "Here is a sentence to embed as a vector"
}'Headers
For information about the required headers, see the Using Generative APIs page.
Body
Required parameters
| Param | Type | Description |
|---|---|---|
input | string or array | Input text to embed, encoded as a string or array of strings. It cannot be an empty string. |
model | string | The name of the model to query. |
Our Embeddings API is OpenAI compatible. Refer to OpenAI’s API reference for detailed information on usage.
Unsupported parameters
encoding_format(default float)dimensions
If you have a use case requiring one of these unsupported parameters, contact us via Slack using the #ai channel.