Generate a model response from text or image inputs. Follows the OpenAI Responses API format, with support for streaming, function and custom tool calls, structured outputs, and reasoning controls.
Generate a model response from text or image inputs. Follows the OpenAI Responses API format, with support for streaming, function and custom tool calls, structured outputs, and reasoning controls.See available models at this pricing table.
The Responses API may not be supported by all models available on Model APIs.
To request successfully, it is mandatory to enter a Personal API Key (e.g. flp_XXX) value in the Bearer Token field.
Refer to the authentication section on our introduction page to learn how to acquire this variable and visit here to generate your API Key.When streaming mode is used (i.e., stream option is set to true), the response is in MIME type text/event-stream. Otherwise, the content type is application/json.
You can view the schema of the streamed sequence of chunk objects in streaming mode here.
This API is currently in Beta.
While we strive to provide a stable and reliable experience, this feature is still under active development.
As a result, you may encounter unexpected behavior or limitations.
We encourage you to provide feedback to help us improve the feature before its official release.
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or top_p but not both.
An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.
Controls which (if any) tool is called by the model. none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools. An object can be used to force the model to call a specific function or custom tool.
An object specifying the format that the model must output. Configuring { "type": "json_schema" } enables Structured Outputs. The default format is { "type": "text" }.
Constrains effort on reasoning for reasoning models. Currently supported values are minimal, low, medium, high, xhigh, max, and ultracode. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.