Alex

Posted on Jul 14

A practical checklist for evaluating an OpenAI-compatible AI API gateway

#tutorial #api #llm #ai

The safest way to test a new AI gateway is not a benchmark prompt.

It is a real workflow, a first successful request, and a small task set.

Disclosure: I am working on modelrouter.site. It is an independent third-party OpenAI-compatible AI API gateway, not an official model-provider service.

1. Choose one workflow

Pick something real:

support answer drafting
lead enrichment
data extraction
summarization
classification
coding assistant task
an agent step in an automation

A generic prompt can tell you whether the endpoint responds. A real workflow tells you whether the route is useful.

2. Run a smoke test first

Use the OpenAI-compatible base URL and one supported model route from your dashboard.

curl https://modelrouter.site/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "copy_a_supported_route_from_your_dashboard",
    "messages": [
      {"role": "user", "content": "Return a one-sentence test response."}
    ]
  }'

Before you compare quality, confirm the basic request works.

Record:

status code
latency
response shape
model route
request ID if available
whether the output is usable

Never paste a full API key into screenshots, support tickets, GitHub issues, or public posts.

3. Run 10-20 real tasks

After the first successful call, run a small task set.

Track:

output usefulness
failure rate
retries
latency range
cost per successful task
whether downstream parsing still works

The key metric is not token price alone. It is cost per useful completed task.

4. Check compatibility details

OpenAI-compatible does not mean every client behaves identically.

Check:

whether the client expects /v1 included in the base URL
exact model ID or model route
streaming vs non-streaming behavior
JSON response shape
timeout behavior
retry handling
error messages that are actually debuggable

These small details matter a lot in n8n, Open WebUI, LibreChat, custom agents, and internal tools.

5. Decide whether to continue

Do not scale because the setup works once.

Scale only if the route is useful for your real task and your team understands billing, logs, fallback behavior, and support paths.

Evaluation link:

https://modelrouter.site/?utm_source=devto&utm_medium=tutorial&utm_campaign=priority_gateway_evaluation

DEV Community