How to govern OpenAI API spend for research agents

1. Why this guide matters

Research agents are often the first place teams see hidden cost growth because they loop, summarize and expand scope faster than expected.

This guide wraps OpenAI usage in a simple NORNR mandate so the workflow can keep moving without losing cost discipline.

2. Install what you need

pip install agentpay langchain-openai

This guide uses the hosted NORNR path at https://nornr.com, so you can validate the decision flow without standing up the full local stack first.

3. Create the governed wallet

from agentpay import Wallet

wallet = Wallet.create(
    owner="research-agent",
    daily_limit=45,
    require_approval_above=18,
    base_url="https://nornr.com",
)

This wallet is the mandate. It sets the budget and review threshold before the framework-specific workflow is allowed to continue.

4. Apply it in the workflow

decision = wallet.pay(
    amount=9.50,
    to="openai",
    purpose="research synthesis",
)

if decision.get("status") == "approved":
    run_research_job()
else:
    print("Research spend held by policy.", decision)

The key pattern stays the same across frameworks: ask NORNR for a decision first, then let the expensive or externally billable step run only if policy says yes.

5. What to expect

• approved means the workflow can continue immediately inside its mandate.
• queued means the request crossed an approval threshold and should wait for review.
• rejected means policy did not allow the action to proceed.

That three-way split is what makes the pattern useful: low-risk work stays fast, higher-risk work becomes reviewable, and clearly out-of-policy work never leaves the workflow.

6. Where to go next

• Hosted quickstart
• Control room
• Guides library