JSON mode

Set response_format: {"type": "json_object"} to constrain output to a single valid JSON object — for extraction, triage scoring, and anything a program consumes downstream.

Cura 1T is a research model, not a medical service, and not a substitute for a clinician. Benchmark scores do not establish safety for unsupervised clinical use.

Example

Always describe the schema you expect in the prompt — JSON mode guarantees syntax, your prompt defines the keys:

Python
import jsonimport osfrom openai import OpenAI client = OpenAI(api_key=os.environ["ACTAVA_API_KEY"], base_url="https://inference.actava.ai/v1") response = client.chat.completions.create(    model="actava/cura-soar",    response_format={"type": "json_object"},    messages=[        {            "role": "system",            "content": (                "Extract structured data. Respond in JSON with keys: "                "chief_complaint (string), red_flags (string[]), triage_level (1-5)."            ),        },        {            "role": "user",            "content": "58F, crushing substernal chest pain radiating to left arm, diaphoretic, 30 min.",        },    ],)data = json.loads(response.choices[0].message.content)print(data["triage_level"])
Output
{  "chief_complaint": "crushing substernal chest pain radiating to left arm",  "red_flags": ["radiation to left arm", "diaphoresis", "duration 30 minutes"],  "triage_level": 1}

Notes

  • Mention "JSON" in your prompt. The request succeeds either way, but if the messages never reference JSON output the object you get back is unpredictable — always state the format and keys explicitly.
  • Truncation produces invalid JSON. If finish_reason is "length", the object was cut off — raise max_tokens rather than attempting repair.
  • Validate downstream. Syntax is guaranteed; clinical semantics are not — check required keys and ranges before acting on the values.
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