Copy, paste, govern.

from openai import OpenAIimport ulid client = OpenAI(    base_url="https://gateway.intsen.example/openai/v1",    api_key=get_intsen_token(),          # OAuth client-credentials token for fleet-advisor-prod    default_headers={        "x-intsen-registration-id": "field-service-assistant-prod",        "x-intsen-agent-id": "field-service/fleet-service-advisor",    },) def handle_user_message(conversation_id: str, user_id: str, messages: list) -> str:    turn_headers = {        "x-intsen-task-id": str(ulid.new()),   # one id per user message, reused for every call in the turn        "x-intsen-conversation-id": conversation_id,        "x-intsen-user-id": user_id,           # IntSen stores only a hash    }    while True:        response = client.chat.completions.create(            model="gpt-5.4-mini", messages=messages, tools=TOOLS, extra_headers=turn_headers)        message = response.choices[0].message        if not message.tool_calls:            return message.content        messages.append(message)        messages.extend(run_tools(message.tool_calls))   # your tools, unchanged

import OpenAI from "openai";import { ulid } from "ulid"; const client = new OpenAI({  baseURL: "https://gateway.intsen.example/openai/v1",  apiKey: await getIntsenToken(),            // OAuth client-credentials token  defaultHeaders: {    "x-intsen-registration-id": "field-service-assistant-prod",    "x-intsen-agent-id": "field-service/fleet-service-advisor",  },}); // One task id per user messageconst turnHeaders = { "x-intsen-task-id": ulid(), "x-intsen-conversation-id": conversationId };const response = await client.chat.completions.create(  { model: "gpt-5.4-mini", messages, tools },  { headers: turnHeaders },);

from langchain_openai import ChatOpenAIimport ulid def model_for_turn(conversation_id: str) -> ChatOpenAI:    # A client per turn keeps the task id simple; reuse it for every call in the turn.    return ChatOpenAI(        model="gpt-5.4-mini",        base_url="https://gateway.intsen.example/openai/v1",        api_key=get_intsen_token(),        default_headers={            "x-intsen-registration-id": "field-service-assistant-prod",            "x-intsen-agent-id": "field-service/fleet-service-advisor",            "x-intsen-task-id": str(ulid.new()),            "x-intsen-conversation-id": conversation_id,        },    )

from openai import AsyncOpenAIfrom agents import set_default_openai_client set_default_openai_client(AsyncOpenAI(    base_url="https://gateway.intsen.example/openai/v1",    api_key=get_intsen_token(),    default_headers={        "x-intsen-registration-id": "field-service-assistant-prod",        "x-intsen-agent-id": "field-service/fleet-service-advisor",    },))# Add x-intsen-task-id per user message using your framework's per-request# header option, or create a client per turn as in the LangChain example.

# Parent agent: pass its task id to the sub-agentresult = await research_agent.run(question, task_id=turn_headers["x-intsen-task-id"]) # Sub-agent: reuse the parent's task id on its own model callsheaders = {"x-intsen-task-id": task_id, "x-intsen-agent-id": "field-service/parts-researcher"}

from openai import APIStatusError try:    response = client.chat.completions.create(        model="gpt-5.4-mini", messages=messages, extra_headers=turn_headers)except APIStatusError as err:    code = (err.body or {}).get("error", {}).get("code")    if code == "task_budget_exceeded":        return "This request needs more steps than allowed. Please narrow it down."    if code in ("model_not_allowed", "provider_not_allowed"):        raise  # configuration problem: check the Registration's models    raise

intsen eval run --agent field-service/fleet-service-advisor --dataset smoke \  --version $COMMIT --adapter "python tests/run_case.py" --junit out/evals.xml

# tests/run_case.py — called once per golden scenario by `intsen eval run`import sys, jsonfrom my_agent import handle_user_message case = json.load(sys.stdin)            # scenario inputanswer = handle_user_message(case["conversation_id"], "ci", case["messages"])print(json.dumps({"answer": answer}))