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List input items

client.beta.responses.inputItems.list(stringresponseID, InputItemListParams { after, include, limit, 2 more } params?, RequestOptionsoptions?): CursorPage<BetaResponseItem>
GET/responses/{response_id}/input_items

Returns a list of input items for a given response.

ParametersExpand Collapse
responseID: string
params: InputItemListParams { after, include, limit, 2 more }
ReturnsExpand Collapse
BetaResponseItem = BetaResponseInputMessageItem { id, content, role, 3 more } | BetaResponseOutputMessage { id, content, role, 4 more } | BetaResponseFileSearchToolCall { id, queries, status, 3 more } | 29 more

Content item used to generate a response.

One of the following:
BetaResponseInputMessageItem { id, content, role, 3 more }
BetaResponseOutputMessage { id, content, role, 4 more }

An output message from the model.

BetaResponseFileSearchToolCall { id, queries, status, 3 more }

The results of a file search tool call. See the file search guide for more information.

BetaResponseComputerToolCall { id, call_id, pending_safety_checks, 5 more }

A tool call to a computer use tool. See the computer use guide for more information.

BetaResponseComputerToolCallOutputItem { id, call_id, output, 5 more }
BetaResponseFunctionToolCallItem extends BetaResponseFunctionToolCall { arguments, call_id, name, 6 more } { id, status, created_by }

A tool call to run a function. See the function calling guide for more information.

BetaResponseFunctionToolCallOutputItem { id, call_id, output, 7 more }
AgentMessage { id, author, content, 3 more }
MultiAgentCall { id, action, arguments, 3 more }
MultiAgentCallOutput { id, action, call_id, 3 more }
BetaResponseToolSearchCall { id, arguments, call_id, 5 more }
BetaResponseToolSearchOutputItem { id, call_id, execution, 5 more }
AdditionalTools { id, role, tools, 2 more }
BetaResponseReasoningItem { id, summary, type, 4 more }

A description of the chain of thought used by a reasoning model while generating a response. Be sure to include these items in your input to the Responses API for subsequent turns of a conversation if you are manually managing context.

Program { id, call_id, code, 3 more }
ProgramOutput { id, call_id, result, 3 more }
BetaResponseCompactionItem { id, encrypted_content, type, 2 more }

A compaction item generated by the v1/responses/compact API.

ImageGenerationCall { id, result, status, 2 more }

An image generation request made by the model.

BetaResponseCodeInterpreterToolCall { id, code, container_id, 4 more }

A tool call to run code.

LocalShellCall { id, action, call_id, 3 more }

A tool call to run a command on the local shell.

LocalShellCallOutput { id, output, type, 2 more }

The output of a local shell tool call.

BetaResponseFunctionShellToolCall { id, action, call_id, 6 more }

A tool call that executes one or more shell commands in a managed environment.

BetaResponseFunctionShellToolCallOutput { id, call_id, max_output_length, 6 more }

The output of a shell tool call that was emitted.

BetaResponseApplyPatchToolCall { id, call_id, operation, 5 more }

A tool call that applies file diffs by creating, deleting, or updating files.

BetaResponseApplyPatchToolCallOutput { id, call_id, status, 5 more }

The output emitted by an apply patch tool call.

McpListTools { id, server_label, tools, 3 more }

A list of tools available on an MCP server.

McpApprovalRequest { id, arguments, name, 3 more }

A request for human approval of a tool invocation.

McpApprovalResponse { id, approval_request_id, approve, 3 more }

A response to an MCP approval request.

McpCall { id, arguments, name, 7 more }

An invocation of a tool on an MCP server.

BetaResponseCustomToolCallItem extends BetaResponseCustomToolCall { call_id, input, name, 5 more } { id, status, created_by }

A call to a custom tool created by the model.

BetaResponseCustomToolCallOutputItem extends BetaResponseCustomToolCallOutput { call_id, output, type, 3 more } { id, status, created_by }

The output of a custom tool call from your code, being sent back to the model.

List input items

import OpenAI from "openai";
const client = new OpenAI();

const response = await client.responses.inputItems.list("resp_123");
console.log(response.data);
{
  "object": "list",
  "data": [
    {
      "id": "msg_abc123",
      "type": "message",
      "role": "user",
      "content": [
        {
          "type": "input_text",
          "text": "Tell me a three sentence bedtime story about a unicorn."
        }
      ]
    }
  ],
  "first_id": "msg_abc123",
  "last_id": "msg_abc123",
  "has_more": false
}
Returns Examples
{
  "object": "list",
  "data": [
    {
      "id": "msg_abc123",
      "type": "message",
      "role": "user",
      "content": [
        {
          "type": "input_text",
          "text": "Tell me a three sentence bedtime story about a unicorn."
        }
      ]
    }
  ],
  "first_id": "msg_abc123",
  "last_id": "msg_abc123",
  "has_more": false
}