Merge branch 'main' into MTA-5092

Author: RoRoJ

ai-data/generative-apis/api-cli/using-chat-api.mdx

@@ -23,7 +23,7 @@ Creates a model response for the given chat conversation.
 curl --request POST \
      --url https://api.scaleway.ai/v1/chat/completions \
      --header 'Authorization: Bearer ${SCW_SECRET_KEY}' \
-     --header 'Content-Type: application/json'
+     --header 'Content-Type: application/json' \
      --data '{
      "model": "llama-3.1-8b-instruct",
      "messages": [

ai-data/generative-apis/api-cli/using-generative-apis.mdx

@@ -20,7 +20,7 @@ dates:
 
 All requests to the Scaleway Generative APIs must include an `Authorization` HTTP header with your API key prefixed by `Bearer`.
 
-We recommend exporting your secret key as an environment variable, which you can then pass directly in your curl request as follows. Remember to replace the example value with your own API secret key.
+We recommend exporting your secret key as an environment variable, which you can then pass directly in your curl request as follows. Remember to replace the example value with *your own API secret key*.
 
 ```
 export SCW_SECRET_KEY=720438f9-fcb9-4ebb-80a7-808ebf15314b

ai-data/generative-apis/how-to/query-text-models.mdx

@@ -54,7 +54,7 @@ from openai import OpenAI
 # Initialize the client with your base URL and API key
 client = OpenAI(
     base_url="https://api.scaleway.ai/v1",  # Scaleway's Generative APIs service URL
-    api_key="<SCW_API_KEY>"  # Your unique API key from Scaleway
+    api_key="<SCW_SECRET_KEY>"  # Your unique API secret key from Scaleway
 )
 ```
 
@@ -69,7 +69,7 @@ response = client.chat.completions.create(
     messages=[{"role": "user", "content": "Describe a futuristic city with advanced technology and green energy solutions."}],
     temperature=0.2,  # Adjusts creativity
     max_tokens=100,   # Limits the length of the output
-    top_p=0.7         # Controls diversity through nucleus sampling
+    top_p=0.7         # Controls diversity through nucleus sampling. You usually only need to use temperature.
 )
 
 # Print the generated response

ai-data/generative-apis/how-to/use-structured-outputs.mdx

@@ -162,6 +162,7 @@ extract = client.chat.completions.create(
     response_format={
         "type": "json_schema",
         "json_schema": {
+            "name": "VoiceNote",
             "schema": VoiceNote.model_json_schema(),
         }
     },
@@ -203,6 +204,7 @@ extract = client.chat.completions.create(
     response_format={
         "type": "json_schema",
         "json_schema": {
+            "name": "VoiceNote", 
             "schema": {
                 "type": "object",
                 "properties": {
@@ -213,6 +215,7 @@ extract = client.chat.completions.create(
                         "items": {"type": "string"}
                     }
                 },
+                "additionalProperties": false,
                 "required": ["title", "summary", "actionItems"]
             }
         }
@@ -235,6 +238,10 @@ Output example:
 }
 ```
 
+<Message type="tip">
+  When using the OpenAI SDKs like in the examples above, you are expected to set `additionalProperties` to false, and to specify all your properties as required.
+</Message>
+
 ## Conclusion
 
 Using structured outputs with LLMs can significantly enhance data handling in your applications.
@@ -243,4 +250,4 @@ By choosing between JSON mode and Structured outputs with JSON schema, you contr
 - **JSON mode** is flexible but less predictable.
 - **Structured outputs** provide strict adherence to a predefined schema, ensuring consistency.
 
-Experiment with both methods to determine which best fits your application's requirements.
+Experiment with both methods to determine which best fits your application's requirements.

ai-data/generative-apis/quickstart.mdx

@@ -55,12 +55,12 @@ pip install openai
 from openai import OpenAI
 
 client = OpenAI(
-    base_url="https://api.scaleway.ai/v1",
-    api_key="<SCW_API_KEY>"
+    base_url="https://api.scaleway.ai/v1", # # Scaleway's Generative APIs service URL
+    api_key="<SCW_SECRET_KEY>" # Your unique API secret key from Scaleway
 )
 ```
 
-Make sure that you replace `<SCW_API_KEY>` with the API key obtained from your Scaleway account.
+Make sure that you replace `<SCW_SECRET_KEY>` with the API key obtained from your Scaleway account.
 
 <Message type="tip">
   It is recommended to store your API keys securely using environment variables or [secret management tools](/identity-and-access-management/secret-manager/) to prevent unauthorized access.

ai-data/managed-inference/reference-content/llama-3-70b-instruct.mdx

@@ -61,7 +61,7 @@ curl -s \
 -H "Authorization: Bearer <IAM API key>" \
 -H "Content-Type: application/json" \
 --request POST \
---url "https://<Deployment UUID>.ifr.fr-par.scw.cloud/v1/chat/completions" \
+--url "https://<Deployment UUID>.ifr.fr-par.scaleway.com/v1/chat/completions" \
 --data '{"model":"llama-3-70b-instruct", "messages":[{"role": "user","content": "Sing me a song about Xavier Niel"}], "max_tokens": 500, "top_p": 1, "temperature": 0.7, "stream": false}'
 ```
 

ai-data/managed-inference/reference-content/llama-3-8b-instruct.mdx

@@ -65,7 +65,7 @@ curl -s \
 -H "Authorization: Bearer <IAM API key>" \
 -H "Content-Type: application/json" \
 --request POST \
---url "https://<Deployment UUID>.ifr.fr-par.scw.cloud/v1/chat/completions" \
+--url "https://<Deployment UUID>.ifr.fr-par.scaleway.com/v1/chat/completions" \
 --data '{"model":"llama-3-8b-instruct", "messages":[{"role": "user","content": "There is a llama in my garden, what should I do?"}], "max_tokens": 500, "top_p": 1, "temperature": 0.7, "stream": false}'
 ```
 

ai-data/managed-inference/reference-content/llama-3.1-70b-instruct.mdx

@@ -60,7 +60,7 @@ curl -s \
 -H "Authorization: Bearer <IAM API key>" \
 -H "Content-Type: application/json" \
 --request POST \
---url "https://<Deployment UUID>.ifr.fr-par.scw.cloud/v1/chat/completions" \
+--url "https://<Deployment UUID>.ifr.fr-par.scaleway.com/v1/chat/completions" \
 --data '{"model":"llama-3.1-70b-instruct", "messages":[{"role": "user","content": "There is a llama in my garden, what should I do?"}], "max_tokens": 500, "temperature": 0.7, "stream": false}'
 ```
 

ai-data/managed-inference/reference-content/llama-3.1-8b-instruct.mdx

@@ -61,7 +61,7 @@ curl -s \
 -H "Authorization: Bearer <IAM API key>" \
 -H "Content-Type: application/json" \
 --request POST \
---url "https://<Deployment UUID>.ifr.fr-par.scw.cloud/v1/chat/completions" \
+--url "https://<Deployment UUID>.ifr.fr-par.scaleway.com/v1/chat/completions" \
 --data '{"model":"llama-3.1-8b-instruct", "messages":[{"role": "user","content": "There is a llama in my garden, what should I do?"}], "max_tokens": 500, "temperature": 0.7, "stream": false}'
 ```
 

ai-data/managed-inference/reference-content/mistral-7b-instruct-v0.3.mdx

@@ -54,7 +54,7 @@ curl -s \
 -H "Authorization: Bearer <IAM API key>" \
 -H "Content-Type: application/json" \
 --request POST \
---url "https://<Deployment UUID>.ifr.fr-par.scw.cloud/v1/chat/completions" \
+--url "https://<Deployment UUID>.ifr.fr-par.scaleway.com/v1/chat/completions" \
 --data '{"model":"mistral-7b-instruct-v0.3", "messages":[{"role": "user","content": "Explain Public Cloud in a nutshell."}], "top_p": 1, "temperature": 0.7, "stream": false}'
 ```