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Co-authored-by: Guillaume Calmettes <[email protected]>
Co-authored-by: Jessica <[email protected]>
Co-authored-by: Benedikt Rollik <[email protected]>

Author: 4 people

macros/ai/chat-comp-vs-responses-api.mdx

@@ -4,8 +4,8 @@ macro: chat-comp-vs-responses-api
 
 Both the [Chat Completions API](https://www.scaleway.com/en/developers/api/generative-apis/#path-chat-completions-create-a-chat-completion) and the [Responses API](https://www.scaleway.com/en/developers/api/generative-apis/#path-responses-beta-create-a-response) are OpenAI-compatible REST APIs that can be used for generating and manipulating conversations. The Chat Completions API is focused on generating conversational responses, while the Responses API is a more general REST API for chat, structured outputs, tool use, and multimodal inputs.
 
-The **Chat Completions** API was released in 2023, and is an industry standard for building AI applications, being specifically designed for handling multi-turn conversations. It is stateless, but allows users to manage conversation history by appending each new message to the ongoing conversation. It supports `function` tool-calling, where the developer defines a set of functions, which the model can decide whether to call when generating a response. If it decides to call one of these functions, it returns the function name and arguments, and the developer's own code must actually execute the function and feed the result back into the conversation for use by the model.
+The **Chat Completions** API was released in 2023, and is an industry standard for building AI applications, being specifically designed for handling multi-turn conversations. It is stateless, but allows users to manage conversation history by appending each new message to the ongoing conversation. Messages in the conversation can include text, images and audio extracts. The API also supports `function` tool-calling, where the developer defines a set of functions, which the model can decide whether to call when generating a response. If it decides to call one of these functions, it returns the function name and arguments, and the developer's own code must actually execute the function and feed the result back into the conversation for use by the model.
 
-The **Responses** API was released in 2025, and is designed to combine the simplicity of Chat Completions with the ability to do more agentic tasks and reasoning. It supports statefulness, being able to maintain context without needing to resend the entire conversation history. It offers tool-calling by built-in tools (e.g. web or file search) that the model is able to execute itself while generating a response, though currently only `function` tools are supported by Scaleway. Overall, **Scaleway's support for the Responses API is currently at beta stage**. All supported Generative API models can be used with Responses API, and note that for the `gtp-oss-120b` model, only the Responses API will allow you to access all of its features. 
+The **Responses** API was released in 2025, and is designed to combine the simplicity of Chat Completions with the ability to do more agentic tasks and reasoning. It supports statefulness, being able to maintain context without needing to resend the entire conversation history. It offers tool-calling by built-in tools (e.g. web or file search) that the model is able to execute itself while generating a response, though currently only `function` tools are supported by Scaleway. Overall, **Scaleway's support for the Responses API is currently at beta stage and the support of the full features set will be incremental**. Most of the supported Generative API models can be used with Responses API, and note that for the **`gtp-oss-120b` model, the use of the Responses API is recommended** as it will allow you to access all of its features, especially tools calling. 
 
 For full details on the differences between these APIs, see the [official OpenAI documentation](https://platform.openai.com/docs/guides/migrate-to-responses).

pages/generative-apis/how-to/query-language-models.mdx

@@ -70,7 +70,7 @@ client = OpenAI(
 
 ### Generating a chat completion
 
-You can now create a chat completion using either the Chat Completions or Responses API, as shown in the following examples: ,
+You can now create a chat completion using either the Chat Completions or Responses API, as shown in the following examples:
 
 <Tabs id="generating-chat-completion">
 

pages/generative-apis/how-to/query-vision-models.mdx

@@ -48,7 +48,7 @@ You can query vision models programmatically using your favorite tools or langua
 
 Vision models take both text and images as inputs.
 
-In the example that follows,we will use the OpenAI Python client.
+In the example that follows, we will use the OpenAI Python client.
 
 <Message type="tip">
   Unlike traditional language models, vision models will take a content array for the user role, structuring text and images as inputs.

pages/generative-apis/how-to/use-structured-outputs.mdx

@@ -41,7 +41,7 @@ There are several ways to interact with language models:
    - JSON mode is older and has been used by developers since early API implementations, but lacks reliability in response formats.
 
 <Message type="note">
-    - All LLMs in the Scaleway library support **Structured outputs** and **JSON mode**. However, a schemaless **JSON mode** will produce lower quality results and is not recommended. Note that structured output is more reliably validated and more richly parsed OKwith the Responses API.
+    - All LLMs in the Scaleway library support **Structured outputs** and **JSON mode**. However, a schemaless **JSON mode** will produce lower quality results and is not recommended. Note that structured output is more reliably validated and more richly parsed with the Responses API.
 </Message>
 
 ## Code examples