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POST
Model-grounded web search (OpenAI).
Ask a question and get an answer that an OpenAI model wrote after searching the live web. Send a Responses request — an input string (or message array) — and the endpoint injects a fixed, server-pinned model and the web_search tool for you; the model, tool and per-request search cap are server-controlled to keep cost bounded. The reply is a standard OpenAI Responses object: output[] contains web_search_call items (each a search that ran) and a message item with the answer text and URL citations, and the billed search count equals the number of web_search_call items. Billing is pay-as-you-go at exact cost: web_search_calls × $0.01 plus the model’s own token cost (fresh input = input_tokens − cached), with no markup. Use this when you want a written, cited answer grounded in current web content from an OpenAI model — for the Anthropic-model equivalent see post_anthropic_websearch_search, and for raw ranked links with extracted page text use post_tavily_search.

Authorizations

Authorization
string
header
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Body

application/json
input
string
required

Your question or instruction, same format as the OpenAI Responses API input. A message array is also accepted.

Example:

"What are the three biggest AI announcements this week? Give one sentence each with sources."

max_output_tokens
integer

Optional cap on the number of tokens generated in the answer.

Example:

1024

instructions
string

Optional high-level instructions to steer the answer's tone or format.

Response

200 - application/json

A standard OpenAI Responses object. output[] interleaves web_search_call items and the cited answer message; the number of web_search_call items is the billed search count.

id
string
object
string
Example:

"response"

status
string
Example:

"completed"

output
object[]

Ordered items: web_search_call (searches performed) and message (the cited answer).

usage
object