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Co-authored-by: Jessica <[email protected]>
Co-authored-by: Néda <[email protected]>

Author: 3 people

pages/generative-apis/how-to/use-function-calling.mdx

@@ -142,7 +142,7 @@ response = client.chat.completions.create(
 print(response.choices[0].message.tool_calls)
 ```
 
-As the model detects properly that a tool call is required to answer the question, the output should be a list of tool calls specifying function names and parameters properties:
+As the model detects properly that a tool call is required to answer the question, the output should be a list of tool calls specifying function names and parameter properties:
 ```bash
 [ChatCompletionMessageToolCall(id='chatcmpl-tool-81e63f4f496d429ba9ec6efcff6a86e1', function=Function(arguments='{"departure_airport": "CDG", "destination_airport": "LHR", "departure_date": "2024-11-01"}', name='get_flight_schedule'), type='function')]
 ```
@@ -335,5 +335,5 @@ For more information about function calling and advanced implementations, refer
 Function calling significantly extends the capabilities of language models by allowing them to interact with external tools and APIs. 
 
 <Message type="note">
-  We cannot wait to see what you will build with function calls. Tell us what you are up to, and share your experiments on Scaleway's [Slack community](https://slack.scaleway.com/) #ai 
+  We cannot wait to see what you will build with function calls. Tell us what you are up to, and share your experiments on Scaleway's [Slack community](https://slack.scaleway.com/) in the #ai channel.
 </Message>