Veja por que o agente fez o que fez, turno a turno, com o que ele leu, chamou e afirmou.

from niadra import Niadra, phone

def shown(product):
    fields = {"price_sale": product["price_sale"]}
    return [{"ref": f"product:store:{product['sku']}", "fields": fields}]

@Niadra.tool("search_products", provenance=shown)
def search_products(sku: str) -> dict:
    return CATALOG[sku]

niadra = Niadra(channel="whatsapp")
customer = phone(customer_phone)
with niadra.conversation(
    thread_id, subject=customer, agent_id="store"
) as conversation:
    conversation.customer(text)
    build = Niadra.build(prompts={"store": "v3"}, model="gpt-4.1-mini")
    with conversation.turn(build=build):
        context = conversation.context(include=["constraints"])
        # recorded: arguments, result, latency, the objects it showed
        product = search_products("PX-4471")
        reply = model(prompt_with(context, product))
        # the record points at this event; the text is never repeated
        conversation.agent(reply)

# Later, in your CI: the recorded turns run again with the pinned build
# niadra replay --agent app.agent:build_agent --scenario <id> --runs 5

• Python
• TypeScript