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Scaleway Managed Inference as drop-in replacement for the OpenAI APIs

Reviewed on 06 March 2024

You can use the OpenAI Python client library to interact with your Scaleway Managed Inference deployment. This feature is especially beneficial for those looking to seamlessly transition applications already utilizing OpenAI.

Chat Completions API

The Chat Completions API is designed for models fine-tuned for conversational tasks (such as X-chat and X-instruct variants).


To invoke Scaleway Managed Inference’s OpenAI-compatible Chat API, simply change the provided endpoint to:

https://<Deployment UUID>

OpenAI Python client library

Use OpenAI’s SDK how you normally would.

from openai import OpenAI
client = OpenAI(
base_url='https://<Deployment UUID>',
api_key='<IAM API key>'
chat_completion =
{ "role": "system",
"content": "You are a helpful assistant."
"role": "user",
"content": "Sing me a song about Scaleway"
model='<Model name>' #e.g 'llama-3-8b-instruct'

More OpenAI-like APIs (e.g audio) will be released step by step once related models are supported.

Supported parameters

  • messages (required)
  • model (required)
  • max_tokens
  • temperature (default 0.7)
  • top_p (default 1)
  • presence_penalty
  • logprobs
  • stop
  • seed
  • stream

Unsupported parameters

Currently, the following options are not supported:

  • response_format
  • frequency_penalty
  • n
  • top_logprobs
  • tools
  • tool_choice
  • logit_bias
  • user

If you have a use case requiring one of these unsupported features, please contact us via Slack.

Embeddings API

The Embeddings API is designed to get a vector representation of an input that can be easily consumed by other machine learning models.


Use your dedicated endpoints as follows:

https://<Deployment UUID>
curl https://<Deployment UUID> \
-H "Authorization: Bearer $SCW_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input": "Embeddings can represent text in a numerical format.",
"model": "$MODEL_NAME"
# model e.g 'sentence-transformers/sentence-t5-xxl:fp32'

OpenAI Python client library

from openai import OpenAI
client = OpenAI(
base_url='https://<Deployment UUID>',
api_key='<IAM API key>'
embedding = client.embeddings.create(
input=["Embeddings can represent text in a numerical format.","Machine learning models use embeddings for various tasks."]
model='<Model name>' #e.g 'sentence-transformers/sentence-t5-xxl:fp32'

Supported parameters

  • input (required) in string or array of strings
  • model (required)

Unsupported parameters

  • encoding_format (default float)
  • dimensions

Future developments

This documentation covers the initial phase of experimental support for the OpenAI API. Gradually, we plan to introduce additional APIs such as:

  • Images API
  • Audio API

We will progressively roll out more OpenAI-like APIs as we expand model support.

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