Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsOne API key and six small tests are enough to learn whether a “compatible” chat endpoint is usable: a known-good request, a missing or invalid key, a key without permission, a malformed body, a streamed response, and a rate-limit or server-failure path. A pass proves only the endpoint, credential, model, request shape and date you tested. It does not prove the service is “OpenAI-compatible” in general.
What a pass can and cannot establish
“OpenAI-compatible” is a claim about a specified interface. It does not guarantee that every parameter, model capability, streaming event or error body matches OpenAI’s. OpenAI documents bearer authentication and a Chat Completions endpoint that generates a response from a list of conversation messages. Its references also describe other API surfaces (Chat Completions and Responses are distinct), changing model behavior, streaming, and separate error categories. Microsoft’s gateway documentation gives one concrete case of a gateway returning the Chat Completions format for supported providers, but that is not evidence of universal compatibility.
So write every result as: endpoint + model + credential/scope + request fields + date → observed behavior. This harness is a design inferred from the vendor documentation. It has not been run against any provider, and the sketch below is illustrative.
Before you start
- Keep the key secret. OpenAI’s API reference says: “Remember that your API key is a secret.” It advises against sharing it or exposing it in browser or app client code, and recommends loading it server-side from an environment variable or key-management service.
- Use a harmless prompt. Something short like “Reply with the word ok.” Avoid sensitive data.
- Record, but never the secret. Log endpoint, model identifier, date, request shape, HTTP result, parsed result and any deviations. Identify the credential by a redacted label or environment name. Keep keys out of logs, screenshots, source control, issue reports and shared traces.
- Note account conditions. Organization or project selection, permissions, account state, model availability and current rate limits can all change results.
- Check the provider’s own docs for the key header and scope. Bearer authentication is the documented pattern for OpenAI’s API, but the target may differ.
The six cases
| # | Case | Accept when | What it establishes |
|---|---|---|---|
| 1 | Known-good non-streaming request | A usable assistant message in the expected shape, not just a success status | Basic access for this exact key, model and route |
| 2 | Missing or invalid key | Rejected and classifiable as an authentication failure | The endpoint actually enforces authentication |
| 3 | Insufficient permissions | Denial is distinguishable from success (and ideally from case 2) | Scope enforcement, where the provider has scoped keys |
| 4 | Malformed or incomplete request | A clear request error is surfaced and handled | Your client copes with that provider’s error shape |
| 5 | Streaming | Incremental events are parsed and a clean end or error is recognized | Streaming works for this target and model |
| 6 | Rate limit or server failure | Never treated as successful output; retry guidance followed | Your failure and retry handling |
1. Known-good non-streaming request
Send a minimal chat request to the documented chat completions route with a valid key and model identifier. Check the body, not only the status: parse the response and confirm an assistant message with non-empty content. Treat an empty or unexpected shape as a failure even on HTTP 200, because this is where “compatible” services most often diverge.
2. Missing or invalid key
Omit the bearer credential, then send a deliberately invalid placeholder such as a string you made up. Confirm rejection and record it as an authentication failure. OpenAI’s error guidance lists invalid, expired or revoked credentials as an authentication error. Don’t reuse a real key with a character changed, and don’t log the attempted value.
3. Insufficient permissions
If the provider supports scoped credentials, use a test credential that lacks a permission the route needs. Confirm the denial is distinguishable from success. OpenAI’s reference notes that a key can lack the permissions an endpoint requires. Scoping mechanics vary by provider. If the provider offers only all-or-nothing keys, mark this case “not applicable” rather than passed.
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4. Malformed or incomplete request
Omit or corrupt a required field, such as model or messages. Verify that a clear request error comes back and that your client surfaces it. Don’t assume the provider uses OpenAI’s error object; record the actual body shape. OpenAI’s troubleshooting guidance distinguishes invalid requests and advises checking that the data is valid and complete.
5. Streaming response
Run this only if streaming is in scope. OpenAI documents Chat Completions streaming as chunks delivered over data-only server-sent events, and its current guide recommends the Responses API for new streaming work. For a compatible chat endpoint, test what the target documents: confirm the client reads incremental chunks, reassembles the text, and recognizes both the normal end and an error that arrives mid-stream. A working non-streaming call says nothing about this path.
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6. Rate limit or server failure
Do not generate costly load on a production account. Use the provider’s safe test facility, or a controlled mock that returns 429 and 5xx responses. Confirm that throttling and server errors are never reported as model output, keep any request IDs and error details, and follow the provider’s retry guidance. OpenAI’s support guidance covers 429 troubleshooting and says its official SDKs retry eligible rate-limit errors and honor Retry-After when present. If you use your own HTTP client, you must implement that behavior yourself.
A skeleton to adapt
This outline shows the shape of the harness. Fill in the base URL, model and header details from your provider’s docs. It is a sketch, not a verified implementation.
- Read
API_KEY,BASE_URLandMODELfrom environment variables. Fail fast if any are missing, and never print the key. - Define a helper that posts JSON to the chat completions route with an
Authorization: Bearerheader (or the provider’s documented equivalent) and returns status, headers of interest and parsed body. - Write one function per case, each returning a record: case number, endpoint, model, date, status, pass/fail/not applicable, and a short note on any deviation.
- For case 5, read the response line by line, handle lines beginning
data:, and stop on the provider’s documented terminator. - For case 6, point the helper at a local mock server instead of the real endpoint.
- Emit the records as a table or JSON, with the credential shown only as a label.
Comparing several endpoints
If you run the same harness against more than one service, line the results up on these axes. They are test dimensions drawn from documented behavior, not a claim that vendors share semantics.
- Base URL and endpoint path
- Authentication header and credential scope
- Accepted model identifiers
- Response schema
- Stream framing, event shape and termination
- Error status and body shape
- Rate-limit and retry signals
How to report the result
State it narrowly, for example: “On 2026-10-06, credential staging-A completed a non-streaming chat request against model X at endpoint Y, was rejected when the key was missing, and streamed correctly. Permission scoping and rate limits were not tested.” Name what was not covered. Different models, other parameters, tool use and later provider changes each need their own checks, and endpoints, models, permission systems and rate limits change, so rerun the harness when any of them does.
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