Responses Types

The Responses API types come from two sources depending on the provider:

• OpenResponses-compliant providers return ResponseResource from the openresponses-types package.
• OpenAI-native providers return Response from the openai SDK.
• Streaming always yields ResponseStreamEvent objects.

Primary Types

ResponseResource

The response object from providers implementing the OpenResponses specification.

Import: from openresponses_types import ResponseResource

Package: openresponses-types

This is the primary return type for OpenResponses-compliant providers. It provides a standardized interface for accessing response content, tool calls, and metadata.

Response

The response object from OpenAI’s native Responses API. Re-exported from openai.types.responses.Response.

Import: from any_llm.types.responses import Response

This is returned by providers that use OpenAI’s API directly (e.g., the openai provider).

ResponseStreamEvent

A single event in a streaming response. Re-exported from openai.types.responses.ResponseStreamEvent.

Import: from any_llm.types.responses import ResponseStreamEvent

Stream events represent incremental updates during response generation, including content deltas, tool call events, and completion signals.

ResponseInputParam

The input type accepted by the input_data parameter of responses() and aresponses(). Re-exported from openai.types.responses.ResponseInputParam.

Import: from any_llm.types.responses import ResponseInputParam

This is typically a list of message items that can include text, images, and tool-related content.

ResponseOutputMessage

An output message within a response. Re-exported from openai.types.responses.ResponseOutputMessage.

Import: from any_llm.types.responses import ResponseOutputMessage

Internal Types

ResponsesParams

Normalized parameters for the Responses API, used internally to pass structured parameters from the public API to provider implementations.

Import: from any_llm.types.responses import ResponsesParams

Field	Type	Description
model	str	Model identifier (e.g., ‘mistral-small-latest’)
input	str | list[EasyInputMessageParam | Message | ResponseOutputMessageParam | ResponseFileSearchToolCallParam | ResponseComputerToolCallParam | ComputerCallOutput | ResponseFunctionWebSearchParam | ResponseFunctionToolCallParam | FunctionCallOutput | ToolSearchCall | ResponseToolSearchOutputItemParamParam | ResponseReasoningItemParam | ResponseCompactionItemParamParam | ImageGenerationCall | ResponseCodeInterpreterToolCallParam | LocalShellCall | LocalShellCallOutput | ShellCall | ShellCallOutput | ApplyPatchCall | ApplyPatchCallOutput | McpListTools | McpApprovalRequest | McpApprovalResponse | McpCall | ResponseCustomToolCallOutputParam | ResponseCustomToolCallParam | ItemReference]	The input payload accepted by provider’s Responses API. For OpenAI-compatible providers, this is typically a list mixing text, images, and tool instructions, or a dict per OpenAI spec.
instructions	str | None
max_tool_calls	int | None
text	Any | None
tools	list[dict[str, Any]] | None	List of tools for tool calling. Should be converted to OpenAI tool format dicts
tool_choice	str | dict[str, Any] | None	Controls which tools the model can call
temperature	float | None	Controls randomness in the response (0.0 to 2.0)
top_p	float | None	Controls diversity via nucleus sampling (0.0 to 1.0)
max_output_tokens	int | None	Maximum number of tokens to generate
response_format	dict[str, Any] | type[pydantic.main.BaseModel] | None	Format specification for the response
stream	bool | None	Whether to stream the response
parallel_tool_calls	bool | None	Whether to allow parallel tool calls
top_logprobs	int | None	Number of top alternatives to return when logprobs are requested
stream_options	dict[str, Any] | None	Additional options controlling streaming behavior
reasoning	dict[str, Any] | None	Configuration options for reasoning models.
presence_penalty	float | None	Penalizes new tokens based on whether they appear in the text so far.
frequency_penalty	float | None	Penalizes new tokens based on their frequency in the text so far.
truncation	str | None	Controls how the service truncates the input when it exceeds the model context window.
store	bool | None	Whether to store the response so it can be retrieved later.
service_tier	str | None	The service tier to use for this request.
user	str | None	A unique identifier representing your end user.
metadata	dict[str, str] | None	Key-value pairs for custom metadata (up to 16 pairs).
previous_response_id	str | None	The ID of the response to use as the prior turn for this request.
include	list[str] | None	Items to include in the response (e.g., ‘reasoning.encrypted_content’).
background	bool | None	Whether to run the request in the background and return immediately.
safety_identifier	str | None	A stable identifier used for safety monitoring and abuse detection.
prompt_cache_key	str | None	A key to use when reading from or writing to the prompt cache.
prompt_cache_retention	str | None	How long to retain a prompt cache entry created by this request.
conversation	str | dict[str, Any] | None	The conversation to associate this response with (ID string or ConversationParam object).

Type Mapping Summary

Type	Source	Used When
ResponseResource	openresponses-types	OpenResponses-compliant providers, non-streaming
Response	openai.types.responses	OpenAI-native providers, non-streaming
ResponseStreamEvent	openai.types.responses	All providers, streaming (stream=True)
ResponseInputParam	openai.types.responses	Input parameter type

For full details on the OpenResponses specification, see the OpenResponses GitHub repository. For OpenAI response types, see the OpenAI Python SDK.