Get Response
Path parameters
Response
Successful Response
The unique identifier of the response. Will be None if store=False.
The object type, which is always 'response'.
The Unix timestamp (in seconds) when the response was created.
The status of the response. Can be 'completed', 'in_progress', 'incomplete', 'failed', or 'cancelled'.
The model used to generate the response (e.g., accounts/<ACCOUNT_ID>/models/<MODEL_ID>).
The ID of the previous response in the conversation, if this response continues a conversation.
Token usage information for the request. Contains 'prompt_tokens', 'completion_tokens', and 'total_tokens'.
Error information if the response failed. Contains 'type', 'code', and 'message' fields.
Details about why the response is incomplete, if status is 'incomplete'. Contains 'reason' field which can be 'max_output_tokens', 'max_tool_calls', or 'content_filter'.
System instructions that guide the model's behavior. Similar to a system message.
The maximum number of tokens that can be generated in the response. Must be at least 1.
The maximum number of tool calls allowed in a single response. Must be at least 1.
Whether to enable parallel function calling during tool use. Default is True.
Reasoning output from the model, if reasoning is enabled. Contains 'content' and 'type' fields.
Whether to store this response for future retrieval. If False, the response will not be persisted and previous_response_id cannot reference it. Default is True.
The sampling temperature to use, between 0 and 2. Higher values like 0.8 make output more random, while lower values like 0.2 make it more focused and deterministic. Default is 1.0.
Text generation configuration parameters, if applicable.
A list of tools the model may call. Each tool is defined with a type and function specification following the OpenAI tool format. Supports 'function', 'mcp', 'sse', and 'python' tool types.
An alternative to temperature sampling, called nucleus sampling, where the model considers the results of tokens with top_p probability mass. So 0.1 means only tokens comprising the top 10% probability mass are considered. Default is 1.0.
The truncation strategy to use for the context. Can be 'auto' or 'disabled'. Default is 'disabled'.
A unique identifier representing your end-user, which can help Fireworks to monitor and detect abuse.
Set of up to 16 key-value pairs that can be attached to the response. Useful for storing additional information about the response in a structured format.