Use the OpenAI client

The coordinator never accepts a plaintext prompt. To use the stock openai package, route it through vorq.sealing_http_client(), a drop-in http_client that seals each Responses request in your process. It is also the SDK's synchronous path: no asyncio needed.

InstallCopy Anchor Link

pip install vorq openai

Set VORQ_WALLET_KEY as in the Quickstart.

Configure the clientCopy Anchor Link

from openai import OpenAI
import vorq

client = OpenAI(
    base_url="https://api.vorq.co/v1",
    api_key="unused",                    # any non-empty string; the wallet authenticates
    http_client=vorq.sealing_http_client(),
)

• sealing_http_client() talks to https://api.vorq.co and signs with VORQ_WALLET_KEY.
• To post a bid that rests until a provider takes it, pass verifier=vorq.Verifier("https://api.vorq.co") as well: such an order is sealed to the coordinator's escrow key, which the client verifies first.

Create a response and wait for itCopy Anchor Link

resp = client.responses.create(
    model="moonshotai/kimi-k3",
    input="Say hello.",
    extra_body={"vorq": {"sla": "batch"}},
)
print(resp.output_text)

Without background, the call blocks until the job settles, for at most the job's sla window. If the job hasn't settled by then, the call raises openai.BadRequestError.

The vorq block carries the order terms the Responses schema has no field for: sla, rate_in, rate_out and an optional provider id.

• sla defaults to "1h" on this path.
• With no rates, the order takes the market: the first provider the coordinator ranks, at its own ask. See Bids and matching.

Create a response in the backgroundCopy Anchor Link

Use background=True whenever the wait might outlive your connection, for example on the "24h" window:

import time

resp = client.responses.create(
    model="moonshotai/kimi-k3",
    input="Summarize the attached notes in three bullet points.",
    background=True,
    extra_body={"vorq": {"sla": "batch"}},
)
job_id = resp.id                      # the response id is the job id; persist it
while resp.status in {"queued", "in_progress"}:
    time.sleep(30)
    resp = client.responses.retrieve(job_id)
print(resp.status, resp.output_text)

In either mode, a job that didn't deliver comes back as a Response with status failed or cancelled and an error object whose code is the cause (provider_fail, reclaim, cancelled or expired). It is not raised as an exception.

client.responses.cancel(job_id) cancels a job no provider has claimed yet. Once a provider has claimed it, the cancel raises openai.ConflictError.

Media and batchesCopy Anchor Link

• A media job comes back as image_generation_call output items, one per frame, with the frame's base64 in result. Video uses the same item type.
• Batches are created with the native client.batches.submit(); the stock client can then retrieve, list and cancel them and read their output files. See Submit a batch.

What doesn't workCopy Anchor Link

• Calling the transport inside a running event loop. It raises, and openai reports an APIConnectionError. In async code, use vorq.Client.
• stream=True, request metadata, and every route other than Responses and a short list of read-only routes. These are refused with a 400 before anything is sent.
• Automatic retries of a failed create. Retry it yourself if you want one.

The full rules, including the forwarded routes and the error mapping, are in the OpenAI transport reference.