OpenAIChatCompletionParameters

The OpenAIChatCompletionParameters class is designed to handle the parameters required for chat completions using the OpenAI API.

Inherits

• OpenAIParameters

Properties

Property	Type	Default Value	Description
model	Text	"gpt-4o-mini"	ID of the model to use.
stream	Boolean	False	Whether to stream back partial progress. If set, tokens will be sent as data-only. Callback formula required.
stream_options	Object	Null	Property for stream=True. For example: {include_usage: True}
max_completion_tokens	Integer	0	The maximum number of tokens that can be generated in the completion.
n	Integer	1	How many completions to generate for each prompt.
temperature	Real	-1	What sampling temperature to use, between 0 and 2. Higher values make the output more random, while lower values make it more focused and deterministic.
store	Boolean	False	Whether or not to store the output of this chat completion request.
reasoning_effort	Text	Null	Constrains effort on reasoning for reasoning models. Currently supported values are "low", "medium", and "high".
response_format	Object	Null	An object specifying the format that the model must output. Compatible with structured outputs.
tools	Collection	Null	A list of tools (OpenAITool) the model may call. Only "function" type is supported.
tool_choice	Variant	Null	Controls which (if any) tool is called by the model. Can be "none", "auto", "required", or specify a particular tool.
prediction	Object	Null	Static predicted output content, such as the content of a text file that is being regenerated.

Asynchronous Callback Properties

Property	Type	Description
onData (or formula)	4D.Function	A function to be called asynchronously when receiving data chunk. Ensure that the current process does not terminate.

onData will receive as argument an OpenAIChatCompletionsStreamResult.

See OpenAIParameters for other callback properties.

Response Format

The response_format parameter allows you to specify the format that the model must output. This is particularly useful when you need structured data or want to ensure the response follows a specific format.

Supported Response Format Types

1. Text Format (Default)

The default response format returns plain text:

var $params := cs.OpenAIChatCompletionsParameters.new({ \
    model: "gpt-4o-mini"; \
    response_format: {type: "text"} \
})

2. JSON Object Format

Forces the model to respond with valid JSON:

var $params := cs.OpenAIChatCompletionsParameters.new({ \
    model: "gpt-4o-mini"; \
    response_format: {type: "json_object"} \
})

var $messages := [ \
    cs.OpenAIMessage.new({ \
        role: "system"; \
        content: "You are a helpful assistant that always responds in JSON format." \
    }) \
]
$messages.push({ \
    role: "user"; \
    content: "Give me information about the number 42 in JSON format with keys 'significance' and 'facts'." \
})

$result := $client.chat.completions.create($messages; $params)

3. JSON Schema Format (Structured Outputs)

For precise control over the JSON structure, you can define a schema:

var $jsonSchema := { \
    type: "object"; \
    properties: { \
        name: {type: "string"}; \
        age: {type: "integer"}; \
        occupation: {type: "string"}; \
        city: {type: "string"} \
    }; \
    required: ["name"; "age"; "occupation"; "city"]; \
    additionalProperties: False \
}

var $params := cs.OpenAIChatCompletionsParameters.new({ \
    model: "gpt-4o-mini"; \
    response_format: { \
        type: "json_schema"; \
        json_schema: { \
            name: "person_info"; \
            description: "Information about a person"; \
            schema: $jsonSchema; \
            strict: True \
        } \
    } \
})

var $messages := [{role: "system"; content: "You are a helpful assistant."}]
$messages.push({ role: "user"; content: "Generate information about a person named John Smith."})

$result := $client.chat.completions.create($messages; $params)

JSON Schema Properties

When using json_schema type, you can specify:

• name: A name for the schema
• description: A description of what the schema represents
• schema: The JSON schema definition
• strict: Whether to enforce strict adherence to the schema

Important Notes

• Not all models support structured outputs (json_object or json_schema), so check model capabilities before using them.
• When using json_object format, you should include instructions in your system message to respond in JSON format
• The json_schema format provides the most control and ensures the response exactly matches your specified structure
• Invalid JSON responses will result in an error when using JSON formats
• JSON schema validation ensures type safety and required field presence

See also

• OpenAIChatCompletionsAPI