API Documentation
A complete implementation guide for integrating AI Shop 24H APIs into production applications with stable routing, predictable cost, and secure key management.
1
Authentication and endpoint structure
Use workspace-scoped API keys and a consistent endpoint structure so your services can authenticate safely and route traffic correctly.
- Store API keys in secure secret managers, never in client bundles.
- Rotate keys periodically and immediately after suspected exposure.
- Separate development, staging, and production keys by workspace.
- Apply per-key limits to contain unexpected traffic spikes.
2
Request format and model selection
Design requests with clear task intent and model selection rules so quality and latency stay consistent across features.
- Use one normalized request payload format for all chat-style flows.
- Define a default model per feature and a controlled fallback list.
- Track response quality by task type before changing model defaults.
- Document model-level constraints so teams avoid invalid assumptions.
3
Errors, retries, and resilience
Production integrations should be resilient to provider-level variance and transient failures.
- Implement timeout and retry with bounded exponential backoff.
- Handle rate-limit and quota errors with explicit user-facing messaging.
- Log request identifiers to speed up incident investigations.
- Use circuit-breaker behavior for repeated downstream failures.
4
Security, monitoring, and governance
Operational visibility and governance controls are required for reliable long-term usage.
- Monitor token usage, latency, and error rates by workspace and key.
- Set budget alerts before limits are reached.
- Restrict key permissions where possible to reduce blast radius.
- Review access logs and billing changes on a regular cadence.