API-REFERENCE STYLE GUIDE

AI API relay: a practical reference for endpoint setup, headers, and smoke tests

This page is written for developers who want a clear way to evaluate an AI API relay, compare routing behavior, and connect OpenAI-style clients without changing their application logic. It also helps teams working with Claude 转发API, 国内直连Claude, and API中转站 workflows.

OpenAI-compatible base URL Manual testing steps Request header checklist Short FAQ

Open the relay portal Review access details

Endpoint

A reliable AI API relay should preserve the upstream-style request shape so your existing SDKs keep working. The main thing to verify is whether the relay accepts standard OpenAI routes, returns consistent error messages, and supports the model names you plan to call. For teams that need a simpler network path, this matters more than marketing claims: you want a stable endpoint, predictable latency, and logs that make debugging possible.

Base URL:
https://59api.com/v1

Typical routes:
POST /chat/completions
POST /responses
GET  /models

Criteria to review before adoption

Compatibility: confirm OpenAI SDK or curl works without custom adapters.
Latency: test a few prompts from your region and note first-token timing.
Model coverage: check whether the relay maps the model IDs you need.
Error handling: make sure HTTP codes and JSON messages are readable.
Operational fit: compare token accounting, rate limits, and request traces.

Example

For a smoke test, start with the smallest useful request. Set the base URL, point your SDK to the relay, and send a short prompt. In shell form, the configuration often looks like this:

export OPENAI_BASE_URL=#/v1
export OPENAI_API_KEY=your_key_here

curl #/v1/chat/completions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model":"gpt-4o-mini",
    "messages":[{"role":"user","content":"Reply with one sentence: relay ok"}]
  }'

Smoke-test steps

Run a /models call to confirm authentication and basic routing.
Send one short chat request and verify the response format matches your SDK.
Repeat the same call three times to compare stability and response time.
Test one larger prompt to see how the relay behaves under slightly heavier input.
Check your app logs for retries, timeouts, or JSON parse errors.

When the relay passes these checks, it is usually ready for a broader integration test. For product teams, the value is not just connectivity; it is whether the relay behaves like a familiar OpenAI-compatible layer so code changes stay minimal. If you need a reference point while reviewing options, compare your results against # as an OpenAI-compatible relay and measure against your own service-level expectations.

FAQ

Is an AI API relay the same as a proxy?

Not exactly. A relay usually emphasizes API compatibility, request forwarding, and developer-facing structure. A plain proxy may only pass traffic through without preserving the API semantics you expect.

Can I use existing OpenAI SDKs?

Yes, if the relay supports standard endpoints and authentication patterns. Set the base URL, keep your request payload normal, and validate the response schema with a short test.

What should I do if a request fails?

Check the API key, endpoint path, model name, and headers first. Then compare the raw response body with the SDK error to identify whether the issue is routing, validation, or upstream behavior.