ResponsesCreateRequest

Request schema for creating a new agent response. Configures the agent's model, input, tools, output format, and behavior. Supports both foreground (blocking) and background (asynchronous) execution with optional streaming.

Example Usage

import { ResponsesCreateRequest } from "@meetkai/mka1/models/components";

let value: ResponsesCreateRequest = {
  model: "meetkai:functionary-urdu-mini-pak",
  input: "What is the capital of France?",
};

Fields

Field	Type	Required	Description
model	string	✔️	The ID of the model to use for generating the response.
input	components.ResponsesCreateRequestInput	➖	The user input to send to the agent. Can be a simple text string for basic queries, or an array of item objects containing text, images, files, or audio for multimodal interactions. This is the main content the agent will respond to.
instructions	string	➖	System or developer instructions inserted into the model's context before user input. Use this to guide the agent's behavior, set personality, define constraints, or provide domain-specific knowledge. Acts as a persistent system message for this response.
conversation	components.ResponsesCreateRequestConversation	➖	The conversation that this response belongs to. Can be a conversation ID string or a conversation object. Used to maintain context and history across multiple agent interactions. Optional - omit for one-off interactions.
previousResponseId	string	➖	The unique ID of a previous response to continue from. Used for multi-turn conversations to maintain context and history. The agent will have access to all previous interactions in the chain.
prompt	components.PromptTemplate	➖	N/A
include	components.Include[]	➖	Additional fields to include in the response output. Allows requesting specific nested data like web search sources, code interpreter outputs, computer screenshots, file search results, input images, output logprobs, or reasoning content. These fields may have performance or cost implications.
text	components.TextConfiguration	➖	N/A
stream	boolean	➖	If set to true, the response data will be streamed using Server-Sent Events (SSE) for real-time updates as the agent generates the response. When false, the response is returned as a single complete object. Defaults to false.
streamOptions	components.ResponsesCreateRequestStreamOptions	➖	Additional options for configuring streaming behavior when stream is enabled.
store	boolean	➖	Whether to store the generated response for later retrieval. When true, the response is saved and can be retrieved via GET /responses/{id}. When false, the response is not persisted after generation. Defaults to true.
background	boolean	➖	Whether to run the model response in the background asynchronously. When true, the request returns immediately with a response ID while the agent processes in the background. Use GET /responses/{id} to retrieve results later. When false, the request blocks until completion. Defaults to false.
webhookUrl	string	➖	URL to receive webhook notifications for status changes (queued, in_progress, completed, failed, incomplete). Only valid when background=true. If provided without background=true, the request will be rejected.
webhookSecret	string	➖	Optional secret for HMAC-SHA256 signing of webhook payloads. When provided, webhooks include an X-Webhook-Signature header with the signature. Requires webhook_url to be set.
tools	components.Tools[]	➖	Array of tool definitions that the agent can use during response generation. Supports built-in tools (web search, file search, code interpreter, computer use, image generation) and custom tools (functions, MCP, local shell). Each tool definition specifies its type and configuration.
toolChoice	components.ToolChoice	➖	N/A
parallelToolCalls	boolean	➖	Whether to allow the agent to execute multiple tool calls in parallel. When true, the agent can make concurrent tool calls for efficiency. When false, tools are called sequentially. Defaults to true for better performance.
maxToolCalls	number	➖	The maximum total number of tool calls the agent can make during this response. Useful for controlling execution time and preventing infinite loops. Applies to all built-in tools like web search, file search, code interpreter, etc. Must be a positive integer between 1 and 300. Defaults to 30.
reasoning	components.ReasoningConfiguration	➖	N/A
autoRouting	boolean	➖	When true, the gateway inspects request complexity and automatically routes between quantized, MoE, and dense variants within the requested model family.
autoRoutingDebug	boolean	➖	Gateway extension. When true alongside auto_routing, the response metadata includes a compact serialized routing decision so you can inspect the inferred target tier even when no compatible sibling variant is available.
maxOutputTokens	number	➖	The maximum number of tokens the model can generate in its output. Sets an upper bound to control costs and response length. The actual output may be shorter if the model finishes naturally. Must be a positive integer.
temperature	number	➖	Controls randomness in the model's output. Higher values (e.g., 1.5-2.0) make output more random and creative, lower values (e.g., 0.0-0.5) make it more focused and deterministic. Must be between 0 and 2.
topP	number	➖	Nucleus sampling parameter. The model considers only the tokens with top_p cumulative probability. Lower values (e.g., 0.1) make output more focused, higher values (e.g., 0.9) allow more diversity. Must be between 0 and 1. Alternative to temperature.
topLogprobs	number	➖	The number of most likely tokens to return at each position along with their log probabilities. Must be between 0 and 20. Useful for understanding model confidence and exploring alternative outputs.
truncation	components.Truncation	➖	The truncation strategy for handling inputs that exceed the model's context window. 'auto' automatically truncates old messages to fit, 'disabled' returns an error if context is too long. Defaults to 'auto'.
contextManagement	components.CompactionContextManagement[]	➖	Array of context management strategies to apply during response generation.
presencePenalty	number	➖	Penalizes new tokens based on whether they appear in the text so far. Higher values increase the model's likelihood to talk about new topics.
frequencyPenalty	number	➖	Penalizes new tokens based on their frequency in the text so far. Higher values decrease the model's likelihood to repeat the same line verbatim.
serviceTier	components.ServiceTier	➖	Specifies the processing tier for serving the request. 'auto' lets the system choose, 'default' uses standard processing, 'flex' allows flexible scheduling for lower priority, 'priority' provides faster processing. Defaults to 'auto'.
promptCacheKey	string	➖	A stable identifier used for caching prompts and context. Helps reduce costs and latency by reusing cached prompt processing. Useful for prompts that are used repeatedly with minor variations.
safetyIdentifier	string	➖	A stable identifier used to help detect and prevent policy violations across multiple requests. Helps the system identify patterns of abuse or misuse. Useful for compliance tracking and safety monitoring.
metadata	Record<string, string>	➖	N/A
modalities	components.Modalities[]	➖	Output types that the model should generate. Defaults to ['text']. Include 'audio' to receive an audio rendering of the text response via TTS.
audio	components.Audio	➖	Audio output configuration. Optional when modalities includes 'audio'; defaults are applied if omitted.
user	string	➖	DEPRECATED: A unique identifier for the end-user. Use safety_identifier for policy violation detection and prompt_cache_key for caching instead. This field is maintained for backwards compatibility.