Agentic Sessions

import uuid

from hiddenlayer import HiddenLayer

client = HiddenLayer()

def call_model(request_payload):
    """Where the call to the model provider is made.

    Takes a request payload and returns the provider's response payload.
    """
    ...

def evaluate_turn(session_id, request_payload):
    """One turn: evaluate the request, call the model, evaluate the response."""
    roundtrip_id = str(uuid.uuid4())  # one per turn; pairs the request with its response

    # Evaluate the request before the model runs. The call returns the request
    # payload to forward (possibly redacted), or a block message if policy blocks it.
    safe_request = client.runtime.evaluate_request(
        body=request_payload,
        hl_runtime_session_id=session_id,
        extra_headers={"HL-Roundtrip-Id": roundtrip_id},
    )
    # Handle BLOCK / REDACT here; omitted for brevity. Forward `safe_request`,
    # which is the (possibly modified) request payload, not an SDK wrapper object.

    model_response = call_model(safe_request)

    # Evaluate the response, reusing the SAME roundtrip id so the two halves pair up.
    safe_response = client.runtime.evaluate_response(
        body=model_response,
        hl_runtime_session_id=session_id,
        extra_headers={"HL-Roundtrip-Id": roundtrip_id},
    )
    # Handle BLOCK / REDACT here too; omitted for brevity.
    return safe_response

def research_subagent(session_id, subtopic):
    """A sub-agent that makes its own model call; it MUST reuse the same session id."""
    return evaluate_turn(session_id, {
        "model": "gpt-4o",
        "messages": [{"role": "user", "content": f"Research this subtopic and summarize findings: {subtopic}"}],
    })

def handle_research_request(question):
    # One session id for the whole research run, created once.
    session_id = str(uuid.uuid4())

    # Turn 1: the lead agent plans the work (same session id).
    evaluate_turn(session_id, {
        "model": "gpt-4o",
        "messages": [{"role": "user", "content": f"Plan the research for: {question}"}],
    })

    # Each sub-agent makes its own model call, all under the SAME session id.
    subtopics = ["background", "current state", "risks"]
    findings = [research_subagent(session_id, subtopic) for subtopic in subtopics]

    # Final turn: the lead composes the report from the findings, still the same session id.
    return evaluate_turn(session_id, {
        "model": "gpt-4o",
        "messages": [{"role": "user", "content": f"Write a report on {question} from: {findings}"}],
    })