Create a messages response. This endpoint is compatible with the Anthropic API.

The maximum number of tokens to generate before stopping. The model may stop before the max_tokens when it reaches the stop sequence.

Model name for the model to use.

If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message.

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. It may not work well with reasoning models.

(Unsupported) When generating next tokens, randomly selecting the next token from the k most likely options.

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. It is generally recommended to alter this or temperature but not both.

Unique object identifier.

Model name that handled the request.

Role of the generated message. Always "assistant"

Reason to stop. "stop_sequence" means the inference has reached a model-defined or user-supplied stop sequence in stop. "max_tokens" means the inference result has reached models' maximum allowed token length or user defined value in max_tokens. "end_turn" or null in streaming mode when the chunk is not the last. "tool_use" means the model has called a tool and is waiting for the tool response.

Custom stop sequence used to stop the generation.

Object type. This is always "message" for message types.