Prevent Margin Leaks & Surprise LLM Bills: Add a Hybrid Spend Firewall

Hi @microsoft,

Love the work on microsoft/qlib! As you transition from open-source into commercializing your AI agent, you'll likely run into a major scaling problem: power users running infinite loops and bankrupting your LLM budget.

Currently, most frameworks require you to pay the Anthropic/OpenAI bill out of pocket or build a complex Stripe billing backend from scratch.

We built NeuForge Pay, a 5-line Python SDK that acts as a proactive Spend Firewall and Hybrid Merchant of Record. It blocks transactions before inference runs if the user exceeds their session budget, and lets them instantly top-up via Stripe (Credit Card) or Coinbase Commerce (USDC on Base for M2M Agent payments).

You can test how fast unmetered agents destroy margins using our interactive calculator here:
NeuForge AI Margin Leak Calculator

Example Integration:

from neuforge_pay import meter_endpoint, neuforge_stripe_webhook, neuforge_coinbase_webhook

# Mount BOTH Fiat and Crypto webhooks
app.include_router(neuforge_stripe_webhook)
app.include_router(neuforge_coinbase_webhook)

@app.get("/v1/agent/task")
@meter_endpoint(price_charged_usd=0.05, model_name="claude-3-5-sonnet", session_budget_usd=10.00)
async def run_agent_task():
    ...

If you are looking to monetize this project without getting burned by unpredictable LLM usage, we'd love for you to try it out!

No qlib file, test, or entry point is identified; first confirm that a billing integration is wanted and define its scope with maintainers. Done would require an accepted design for spend limits, payment providers, and integration boundaries, none of which this issue specifies.