OpenAI SDK setup
Point an SDK at TackleKey with base_url and one model name.
TackleKey
AI agent cost control
AI agents need cost controls before they need more models
Agent loops can turn one user action into many model calls. Before scaling an agent, separate project keys, cap first tests, verify model pricing, and inspect request logs.
Execution order
| # | Action | Why it matters |
|---|---|---|
| 1 | Create an isolated project key | Use a dedicated key for the agent so experiments, production traffic, and customer projects do not share one budget. |
| 2 | Start with a small model and prompt | Run one controlled task first. Avoid enabling tool loops or retrieval loops before logs are easy to read. |
| 3 | Watch successful-request cost | Compare the cost of successful completions, not only token list price. |
| 4 | Review errors before fallback | A fallback route can hide failures and create extra spend. Check the first error in logs before adding more routes. |
Related resources
Route candidates
Start from cheaper public candidates, then verify behavior.
429 troubleshooting
Tune retries and request rates before a loop scales.
This is a scenario checklist, not a lowest-price or availability guarantee. Confirm live pricing, logs, and service boundaries before scaling.
Try TackleKey with one OpenAI-compatible change
Create an account, generate a project API key, then replace your client base URL with the TackleKey endpoint. Keep keys server-side and verify live pricing before scaling traffic.