Decisions API

vLLM provides a text-only implementation of OpenAI's POST /v1/decisions API. Start a supported model:

vllm serve Qwen/Qwen3-0.6B

from openai import OpenAI

client = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY")
decision = client.decisions.create(
    model="Qwen/Qwen3-0.6B",
    input="The package arrived with a broken screen.",
    questions=[
        {
            "type": "predicate",
            "name": "damaged",
            "instructions": "Does the customer report a damaged item?",
        },
        {
            "type": "choice",
            "name": "department",
            "instructions": "Which department should handle this complaint?",
            "choices": [{"value": "returns"}, {"value": "billing"}],
        },
        {
            "type": "score",
            "instructions": "How severe is the damage?",
            "levels": [{"label": "cosmetic"}, {"label": "broken"}],
        },
    ],
)
print(decision.answers)

Use OpenAI Python SDK 3.26.0 or newer for client.decisions.create. input accepts a string or an array of user messages with string content or input_text parts. Answers retain question order and echo name, including null for unnamed questions. Choice values preserve strings and booleans. Scores are probability-weighted averages of zero-based level indices.

The request contract follows the OpenAI OpenAPI schemas retrieved on October 7, 2026. This MVP supports 1–64 questions, 2–26 choices, and 2–10 score levels. Upstream permits 200 questions and 255 choices; this backend returns a 400 when either model limit is exceeded. The optional safety_identifier is caller metadata, available in request body logging with --enable-log-requests and DEBUG logging; it does not authenticate callers.

Implementation and limits

This MVP uses the same label-reading backend as structured decisions. It supports generation architectures with a registered read strategy, including Qwen, DiffusionGemma, and Liquid d1; unsupported models return 501. Each question reads a model's label tokens. Usage reports the actual prompt and output tokens across these reads, including prefix-cache counters.

Probabilities are normalized over the supplied options. confidence is the winning label's probability over the full vocabulary; it is not calibrated to OpenAI's models. Thinking is disabled for these reads.

Image inputs, other message roles, tools, streaming, and per-question refusal scoring are outside this MVP. Unsupported request fields and input types are rejected. The /v1/systemone endpoint retains its existing request format and is available by default.